{"id":"ce167a5c-a404-4670-9458-02d2dd8d0bd6","entityType":"agent","slug":"clawhub-dataify-server-dataify-amazon-product-list","name":"Dataify Amazon Product List","canonicalUrl":"https://www.xpersona.co/agent/clawhub-dataify-server-dataify-amazon-product-list","canonicalPath":"/agent/clawhub-dataify-server-dataify-amazon-product-list","generatedAt":"2026-10-11T10:49:26.905Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T08:15:15.060Z","emptyReason":null},"description":"Collect Amazon Product List data and return results","descriptionLabel":"Source description","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. 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execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T08:15:15.060Z","emptyReason":null},"readme":"Skill: Dataify Amazon Product List\n\nOwner: dataify-server\n\nSummary: Collect Amazon Product List data and return results\n\nTags: latest:1.3.1\n\nVersion history:\n\nv1.3.1 | 2026-09-08T06:17:38.744Z | user\n\nFix natural-language usage failures: validate required targets and URLs, preserve catalog references, default Amazon region safely, normalize Google News links, and improve UTF-8 error output.\n\nv1.3.0 | 2026-09-01T09:12:13.070Z | user\n\n默认返回最终采集结果，完善异步等待下载与安全恢复；修复空目标误执行、Quick Start、Token 配置和触发路由冲突，并补齐发布前自动化测试\n\nv1.2.0 | 2026-07-16T08:35:14.154Z | user\n\n新增能力路由与异步任务闭环，修复失效引用、Token 泄漏和 Skill 元数据兼容性\n\nv1.1.0 | 2026-06-08T02:05:27.197Z | user\n\n补全中文文档，更新目录结构\n\nv1.0.0 | 2026-05-28T06:31:03.571Z | auto\n\n- Initial release of dataify-amazon-product-list skill.\n- Supports submitting Amazon product list collection jobs via Dataify Builder by keyword and domain.\n- Handles API TOKEN resolution, including prompts if missing and instructions for environment variable setup.\n- Confirms and displays user-provided parameters in a Markdown table before submitting jobs.\n- Includes detailed troubleshooting messages for missing or invalid input fields.\n- On success, returns the task_id and directs users to view results at https://dataify.com/dashboard/.\n\nArchive index:\n\nArchive v1.3.1: 12 files, 31931 bytes\n\nFiles: agents/openai.yaml (418b), scripts/business_workflow.py (34775b), scripts/catalog_builder.py (7013b), scripts/dataify_client.py (6994b), scripts/submit_amazon_product_list.py (5518b), scripts/task_runtime.py (2259b), scripts/token_setup.py (2585b), scripts/wait_for_task.py (8879b), skill-card.md (2521b), SKILL.md (8005b), SKILL.zh-CN.md (7784b), _meta.json (146b)\n\nFile v1.3.1:SKILL.md\n\n---\nname: dataify-amazon-product-list\ndescription: \"Collect Amazon product-list records by keyword and marketplace domain. Use when both list-style results and a target Amazon domain are required. Do not use for a single ASIN, product details, reviews, or global brand collection.\"\n---\n\n# Dataify Amazon Product List\n\nSubmit Amazon product list collection jobs by keyword and domain through Dataify Builder and continue through final-result retrieval. After submission, continue monitoring the returned `task_id` and return the final result by default.\n\n\n## Quick Start\n\n**Input:** a keyword and Amazon domain.\n\n```bash\npython3 scripts/submit_amazon_product_list.py --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1\n```\n\nThe command waits up to 10 minutes and prints the final JSON result. Add `--no-wait` only for submission-only behavior.\n\nIf `DATAIFY_API_TOKEN` is missing, log in or register at https://dashboard.dataify.com/login?utm_source=skill. New accounts get 50 free credits, enough for about 6,000 trial results, valid for 7 days, and only successful requests are billed.\n\n## API TOKEN Handling\n\nUse `DATAIFY_API_TOKEN` as the long-term saved token name.\n\n- If `DATAIFY_API_TOKEN` is saved locally, use it.\n- Do not call the Builder endpoint without a token.\n- Always call it `API TOKEN` in user-facing instructions. Prefer the environment variable name `DATAIFY_API_TOKEN` for saved local use.\n\nPowerShell examples for saving the token for the current session:\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\nFor a persistent user-level variable on Windows:\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## Core Workflow\n\n3. Ask: \"Do you want to change any of these values before I submit the task?\"\n4. Normalize the final values into `keyword`, `domain`, `page_turning`, and `file_name`.\n7. Validate required fields and numeric constraints.\n8. Submit a Builder request to create the task.\n9. Read `data.task_id` from the Builder response.\n\n## Parameter Checklist\n\n| Field | Required | Default | Notes |\n| --- | --- | --- | --- |\n| `keyword` | Yes | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon product-list keyword query. |\n| `domain` | Yes | `https://www.amazon.com/` | Amazon domain. |\n| `page_turning` | No | `1` | Number of pages to collect. Must be an integer greater than or equal to `0`. |\n| `file_name` | No | `{{TasksID}}` | Builder form field. Can be changed by the user. |\n\nIf the user has already provided some values, show those values in place of the defaults and only ask whether the remaining/defaulted values should be changed.\n\n## Dataify Builder Request\n\nUse form fields rather than hand-built URL-encoded strings.\n\n- URL: `https://scraperapi.dataify.com/builder`\n- Method: `POST`\n- Authorization header: `Bearer DATAIFY_API_TOKEN`\n- Content type: `application/x-www-form-urlencoded`\n- Fixed fields:\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- Dynamic fields:\n  - `spider_parameters` must be a JSON string, not a raw object.\n  - `file_name` defaults to `{{TasksID}}` and can be changed by the user.\n\n## Script\n\nFor stable execution, prefer `scripts/submit_amazon_product_list.py` with Python 3.6 or newer instead of rewriting the Builder flow. The script writes and reads UTF-8 text.\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\nThe script prints a JSON summary with `task_id`, `keyword`, `domain`, `page_turning`, `file_name` and `message`.\n\n## Troubleshooting\n\n`Missing Dataify API TOKEN` means `DATAIFY_API_TOKEN` is not set in the environment. Tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n\n`Keyword cannot be empty` means no usable keyword query was provided.\n\n`Domain cannot be empty` means no usable domain was provided.\n\n`Page turning must be greater than or equal to 0` means the numeric page count is invalid.\n\n`File name cannot be empty` means no usable `file_name` was provided.\n\nMissing `task_id` usually means the authorization header, token, `spider_name`, or `spider_id` is wrong.\n\n## Guardrails\n\n- Do not invent result fields.\n\n## Default completion behavior\n\nThe default deliverable is the collected result, not only a `task_id`.\n\n1. Submit the Builder task once and capture its `task_id`.\n2. Immediately continue with `$dataify-task-operations` and monitor the same task ID.\n   - Use the default 600-second wait for ordinary collections.\n   - Use `--timeout 1800` for media downloads or clearly high-volume, multi-page, or multi-input collections.\n3. When the task succeeds, download and return the final JSON result. Summarize large payloads while preserving access to the raw result.\n4. If monitoring times out or is interrupted, return the task ID and a resume command. Do not resubmit the paid task.\n5. Stop after submission only when the user explicitly asks for submission only, a task ID, or `--no-wait` behavior.\n\n## Parameter interaction policy\n\n- For a clear, low-risk, read-only, and low-cost request, apply safe defaults and execute immediately. A short execution summary is optional; do not pause for confirmation.\n- Ask only for a missing required input, a material ambiguity, a high-volume or multi-page scope, a media download, a choice that materially changes credit usage, an irreversible action, or an explicit user request to review parameters.\n- When confirmation is required, show only user-facing values that affect the target, scope, output, or cost. Prefer one concise sentence; use a compact table only when three or more consequential values are easier to compare.\n- Never show fixed fields, empty optional fields, unchanged defaults, credentials, or internal implementation parameters such as engine selectors, response-format flags, offsets, spider IDs, and file-name templates.\n- Keep advanced filters hidden unless the user asks for them or they are needed to resolve ambiguity. Never substitute documentation example values for missing required user input.\n- After returning results, offer relevant refinements instead of forcing all optional decisions before the first result.\n\n## Account CTA policy\n\n- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.\n- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts get 50 free credits, enough for about 6,000 trial results, valid for 7 days, and only successful requests are billed. Never ask the user to paste the token into chat.\n- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.\n- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.\n- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.\n- For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.\n- During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.\n\nFile v1.3.1:_meta.json\n\n{\n  \"ownerId\": \"kn74z5hmmwk21kw8tpphd9w21x86bkdf\",\n  \"slug\": \"dataify-amazon-product-list\",\n  \"version\": \"1.3.1\",\n  \"publishedAt\": 1788848258744\n}\n\nFile v1.3.1:skill-card.md\n\n## Description:\n\nCollect Amazon product-list records by keyword and marketplace domain through Dataify Builder and return the collected JSON result.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[dataify-server](https://clawhub.ai/user/dataify-server)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and operators use this skill to submit Dataify Amazon product-list collection jobs by keyword and Amazon marketplace domain, then monitor the task and retrieve final JSON results. It is intended for list-style Amazon collection, not single-ASIN details, reviews, or global brand collection.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill requires a Dataify account token and can submit paid or credit-consuming Dataify jobs.\n\nMitigation: Configure DATAIFY_API_TOKEN through the local environment, do not expose token values in chat or logs, and confirm high-volume or multi-page collection scopes before execution.\n\nRisk: Security evidence reports credential and import-handling risks, including token-in-query and external import-path behavior.\n\nMitigation: Review, fix, or explicitly accept these behaviors before installation; run the skill in a least-privileged environment until resolved.\n\nRisk: Security evidence reports broader under-disclosed scraping and business-intelligence helper code beyond the advertised Amazon-list workflow.\n\nMitigation: Review the bundled scripts before deployment and restrict invocation to the advertised Amazon product-list workflow unless the additional helpers are intentionally approved.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/dataify-server/skills/dataify-amazon-product-list)\n- [Dataify dashboard](https://dashboard.dataify.com?utm_source=skill)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]\n\n**Output Format:** [Markdown guidance with shell commands and JSON task/result output]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires DATAIFY_API_TOKEN; normal execution can submit credit-consuming Dataify jobs and may wait for asynchronous task completion.]\n\n## Skill Version(s):\n\n1.3.1 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.3.1:SKILL.zh-CN.md\n\n---\nname: dataify-amazon-product-list\ndescription: \"用于 Dataify Amazon 商品列表采集 Builder 任务。当用户说到或请求 Amazon 产品列表采集工具、Amazon product list collection/tool/scraping，或按 keyword and domain 采集 Amazon product list 时触发。支持创建 amazon_product-list_by-keywords-domain 任务、返回 task_id、配置或复用 DATAIFY_API_TOKEN，并排查 Dataify Builder 请求失败。\"\n---\n\n# Dataify Amazon Product List\n\n通过 Dataify Builder 按关键词和域名提交 Amazon 产品列表采集任务，提交后停止。成功提交后，将 `task_id` 提供给用户，并告知他们前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看结果。\n\n## API TOKEN 处理\n\n使用 `DATAIFY_API_TOKEN` 作为长期保存的 token 名称。\n\n- 如果用户在请求中提供了 token，则在本次运行中使用该 token。\n- 如果未提供 token，先检查环境变量中是否已保存 `DATAIFY_API_TOKEN`。\n- 如果本地已保存 `DATAIFY_API_TOKEN`，则直接使用。\n- 如果本地没有可用的 token，告诉用户：`Dataify 需要 API Token。新账号注册即得 50 免费积分，约可获得 6000 条试用结果，7 天有效，仅成功请求计费。注册完成后告诉我，我会继续当前任务。`。\n- 没有 token 不要调用 Builder 接口。\n- 在面向用户的说明中始终称其为 `API TOKEN`。在本地保存使用时，优先使用环境变量名 `DATAIFY_API_TOKEN`。\n\nPowerShell 示例，为当前会话保存 token：\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\n在 Windows 上设置持久的用户级变量：\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## 核心工作流程\n\n3. 询问：\"在我提交任务之前，您是否需要修改这些值？\"\n4. 将最终值规范化为 `keyword`、`domain`、`page_turning` 和 `file_name`。\n5. 从用户明确提供的输入或已保存的 `DATAIFY_API_TOKEN` 中获取 Dataify token。\n6. 如果没有可用的 token，告诉用户：`Dataify 需要 API Token。新账号注册即得 50 免费积分，约可获得 6000 条试用结果，7 天有效，仅成功请求计费。注册完成后告诉我，我会继续当前任务。`。\n7. 验证必填字段和数值约束。\n8. 提交 Builder 请求创建任务。\n9. 从 Builder 响应中读取 `data.task_id`。\n10. 告诉用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看或管理结果。\n\n## 参数清单\n\n| 字段 | 必填 | 默认值 | 说明 |\n| --- | --- | --- | --- |\n| `keyword` | 是 | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon 产品列表关键词查询。 |\n| `domain` | 是 | `https://www.amazon.com/` | Amazon 域名。 |\n| `page_turning` | 否 | `1` | 采集的页数。必须是大于等于 `0` 的整数。 |\n| `file_name` | 否 | `{{TasksID}}` | Builder 表单字段。可由用户修改。 |\n\n如果用户已经提供了部分值，在表格中显示这些值代替默认值，只询问是否需要修改剩余/使用默认值的参数。\n\n## Dataify Builder 请求\n\n使用表单字段而不是手动构建的 URL 编码字符串。\n\n- URL：`https://scraperapi.dataify.com/builder`\n- 方法：`POST`\n- Authorization 头：`Bearer DATAIFY_API_TOKEN`\n- Content type：`application/x-www-form-urlencoded`\n- 固定字段：\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- 动态字段：\n  - `spider_parameters` 必须是 JSON 字符串，不能是原始对象。\n  - `file_name` 默认为 `{{TasksID}}`，可由用户修改。\n\n## 脚本\n\n为确保稳定执行，建议使用 Python 3.6 或更新版本运行 `scripts/submit_amazon_product_list.py`，而不是重写 Builder 流程。脚本使用 UTF-8 编码进行读写。\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\n脚本会输出包含 `task_id`、`keyword`、`domain`、`page_turning`、`file_name`、`dashboard_url` 和 `message` 的 JSON 摘要。\n\n## 故障排除\n\n`Missing Dataify API TOKEN` 表示没有传入明确的 token 且本地未保存 `DATAIFY_API_TOKEN`。告诉用户：`Dataify 需要 API Token。新账号注册即得 50 免费积分，约可获得 6000 条试用结果，7 天有效，仅成功请求计费。注册完成后告诉我，我会继续当前任务。`。\n\n`Keyword cannot be empty` 表示没有提供有效的关键词查询。\n\n`Domain cannot be empty` 表示没有提供有效的域名。\n\n`Page turning must be greater than or equal to 0` 表示页数数值无效。\n\n`File name cannot be empty` 表示没有提供有效的 `file_name`。\n\n缺少 `task_id` 通常表示 authorization 头、token、`spider_name` 或 `spider_id` 有误。\n\n## 注意事项\n\n- 不要编造结果字段。\n- 成功创建任务后，始终引导用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill)。\n\n## 参数交互策略\n\n- 当请求意图明确、只读、低风险且成本较低时，使用安全默认值直接执行。可以用一句话说明执行内容，但不要暂停等待确认。\n- 只在缺少必填输入、存在会明显改变结果的歧义、大批量或多页采集、媒体下载、会明显增加积分消耗、不可逆操作，或用户明确要求查看参数时询问。\n- 必须确认时，只展示会影响目标、范围、输出或成本的用户参数。优先使用一句简短说明；只有三个及以上关键值确实需要比较时才使用精简表格。\n- 不要展示固定字段、空的可选字段、未修改的默认值、凭据或内部实现参数，例如引擎选择、响应格式开关、偏移量、spider ID 和文件名模板。\n- 默认隐藏高级筛选项，除非用户主动询问或需要它们消除歧义。不得用文档示例值代替用户缺失的必填输入。\n- 先返回首个结果，再提供相关的细化选项，不要在首次执行前强迫用户决定所有可选项。\n\n## Account CTA policy\n\n- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.\n- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts get 50 free credits, enough for about 6,000 trial results, valid for 7 days, and only successful requests are billed. Never ask the user to paste the token into chat.\n- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.\n- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.\n- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.\n- For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.\n- During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.\n\nFile v1.3.1:agents/openai.yaml\n\ninterface:\n  display_name: \"Dataify Amazon Product List\"\n  short_description: \"Collect Amazon Product List data and return results\"\n  default_prompt: \"Use $dataify-amazon-product-list to complete the requested Dataify collection, wait for the asynchronous task, and return the final collected result. Stop at task submission only when I explicitly request no-wait behavior.\"\n\npolicy:\n  allow_implicit_invocation: true\n\nArchive v1.3.0: 6 files, 10942 bytes\n\nFiles: agents/openai.yaml (418b), scripts/submit_amazon_product_list.py (5402b), skill-card.md (1843b), SKILL.md (7819b), SKILL.zh-CN.md (7334b), _meta.json (146b)\n\nFile v1.3.0:SKILL.md\n\n---\nname: dataify-amazon-product-list\ndescription: \"Collect Amazon product-list records by keyword and marketplace domain. Use when both list-style results and a target Amazon domain are required. Do not use for a single ASIN, product details, reviews, or global brand collection.\"\n---\n\n# Dataify Amazon Product List\n\nSubmit Amazon product list collection jobs by keyword and domain through Dataify Builder and continue through final-result retrieval. After submission, continue monitoring the returned `task_id` and return the final result by default.\n\n\n## Quick Start\n\n**Input:** a keyword and Amazon domain.\n\n```bash\npython3 scripts/submit_amazon_product_list.py --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1\n```\n\nThe command waits up to 10 minutes and prints the final JSON result. Add `--no-wait` only for submission-only behavior.\n\nIf `DATAIFY_API_TOKEN` is missing, log in or register at https://dashboard.dataify.com/login?utm_source=skill. New accounts receive 50 free credits.\n\n## API TOKEN Handling\n\nUse `DATAIFY_API_TOKEN` as the long-term saved token name.\n\n- If `DATAIFY_API_TOKEN` is saved locally, use it.\n- Do not call the Builder endpoint without a token.\n- Always call it `API TOKEN` in user-facing instructions. Prefer the environment variable name `DATAIFY_API_TOKEN` for saved local use.\n\nPowerShell examples for saving the token for the current session:\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\nFor a persistent user-level variable on Windows:\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## Core Workflow\n\n3. Ask: \"Do you want to change any of these values before I submit the task?\"\n4. Normalize the final values into `keyword`, `domain`, `page_turning`, and `file_name`.\n7. Validate required fields and numeric constraints.\n8. Submit a Builder request to create the task.\n9. Read `data.task_id` from the Builder response.\n\n## Parameter Checklist\n\n| Field | Required | Default | Notes |\n| --- | --- | --- | --- |\n| `keyword` | Yes | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon product-list keyword query. |\n| `domain` | Yes | `https://www.amazon.com/` | Amazon domain. |\n| `page_turning` | No | `1` | Number of pages to collect. Must be an integer greater than or equal to `0`. |\n| `file_name` | No | `{{TasksID}}` | Builder form field. Can be changed by the user. |\n\nIf the user has already provided some values, show those values in place of the defaults and only ask whether the remaining/defaulted values should be changed.\n\n## Dataify Builder Request\n\nUse form fields rather than hand-built URL-encoded strings.\n\n- URL: `https://scraperapi.dataify.com/builder`\n- Method: `POST`\n- Authorization header: `Bearer DATAIFY_API_TOKEN`\n- Content type: `application/x-www-form-urlencoded`\n- Fixed fields:\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- Dynamic fields:\n  - `spider_parameters` must be a JSON string, not a raw object.\n  - `file_name` defaults to `{{TasksID}}` and can be changed by the user.\n\n## Script\n\nFor stable execution, prefer `scripts/submit_amazon_product_list.py` with Python 3.6 or newer instead of rewriting the Builder flow. The script writes and reads UTF-8 text.\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\nThe script prints a JSON summary with `task_id`, `keyword`, `domain`, `page_turning`, `file_name` and `message`.\n\n## Troubleshooting\n\n`Missing Dataify API TOKEN` means `DATAIFY_API_TOKEN` is not set in the environment. Tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n\n`Keyword cannot be empty` means no usable keyword query was provided.\n\n`Domain cannot be empty` means no usable domain was provided.\n\n`Page turning must be greater than or equal to 0` means the numeric page count is invalid.\n\n`File name cannot be empty` means no usable `file_name` was provided.\n\nMissing `task_id` usually means the authorization header, token, `spider_name`, or `spider_id` is wrong.\n\n## Guardrails\n\n- Do not invent result fields.\n\n## Default completion behavior\n\nThe default deliverable is the collected result, not only a `task_id`.\n\n1. Submit the Builder task once and capture its `task_id`.\n2. Immediately continue with `$dataify-task-operations` and monitor the same task ID.\n   - Use the default 600-second wait for ordinary collections.\n   - Use `--timeout 1800` for media downloads or clearly high-volume, multi-page, or multi-input collections.\n3. When the task succeeds, download and return the final JSON result. Summarize large payloads while preserving access to the raw result.\n4. If monitoring times out or is interrupted, return the task ID and a resume command. Do not resubmit the paid task.\n5. Stop after submission only when the user explicitly asks for submission only, a task ID, or `--no-wait` behavior.\n\n## Parameter interaction policy\n\n- For a clear, low-risk, read-only, and low-cost request, apply safe defaults and execute immediately. A short execution summary is optional; do not pause for confirmation.\n- Ask only for a missing required input, a material ambiguity, a high-volume or multi-page scope, a media download, a choice that materially changes credit usage, an irreversible action, or an explicit user request to review parameters.\n- When confirmation is required, show only user-facing values that affect the target, scope, output, or cost. Prefer one concise sentence; use a compact table only when three or more consequential values are easier to compare.\n- Never show fixed fields, empty optional fields, unchanged defaults, credentials, or internal implementation parameters such as engine selectors, response-format flags, offsets, spider IDs, and file-name templates.\n- Keep advanced filters hidden unless the user asks for them or they are needed to resolve ambiguity. Never substitute documentation example values for missing required user input.\n- After returning results, offer relevant refinements instead of forcing all optional decisions before the first result.\n\n## Account CTA policy\n\n- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.\n- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.\n- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.\n- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.\n- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.\n- For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.\n- During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.\n\nFile v1.3.0:_meta.json\n\n{\n  \"ownerId\": \"kn74z5hmmwk21kw8tpphd9w21x86bkdf\",\n  \"slug\": \"dataify-amazon-product-list\",\n  \"version\": \"1.3.0\",\n  \"publishedAt\": 1788253933070\n}\n\nFile v1.3.0:skill-card.md\n\n## Description:\n\nCollect Amazon product-list records by keyword and marketplace domain.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[dataify-server](https://clawhub.ai/user/dataify-server)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and agents use this skill to submit Dataify Amazon product-list collection jobs for a keyword and marketplace domain, wait for asynchronous completion, and return collected JSON results.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Submitting collection jobs uses a Dataify API token and may consume Dataify credits.\n\nMitigation: Use a dedicated Dataify API token and confirm collection scope, such as page count, before high-volume runs.\n\nRisk: Persisting the Dataify API token on shared or untrusted machines could expose account credentials.\n\nMitigation: Prefer session-scoped token configuration on shared systems and never print or paste the token into chat.\n\n## Reference(s):\n\n- [ClawHub Skill Page](https://clawhub.ai/dataify-server/skills/dataify-amazon-product-list)\n- [Dataify Dashboard](https://dashboard.dataify.com?utm_source=skill)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Shell commands, Configuration, Guidance]\n\n**Output Format:** [Markdown guidance with shell commands and JSON task/result payloads]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Returns task metadata and, by default, monitors the Dataify task for final JSON results.]\n\n## Skill Version(s):\n\n1.3.0 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.3.0:SKILL.zh-CN.md\n\n---\nname: dataify-amazon-product-list\ndescription: \"用于 Dataify Amazon 商品列表采集 Builder 任务。当用户说到或请求 Amazon 产品列表采集工具、Amazon product list collection/tool/scraping，或按 keyword and domain 采集 Amazon product list 时触发。支持创建 amazon_product-list_by-keywords-domain 任务、返回 task_id、配置或复用 DATAIFY_API_TOKEN，并排查 Dataify Builder 请求失败。\"\n---\n\n# Dataify Amazon Product List\n\n通过 Dataify Builder 按关键词和域名提交 Amazon 产品列表采集任务，提交后停止。成功提交后，将 `task_id` 提供给用户，并告知他们前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看结果。\n\n## API TOKEN 处理\n\n使用 `DATAIFY_API_TOKEN` 作为长期保存的 token 名称。\n\n- 如果用户在请求中提供了 token，则在本次运行中使用该 token。\n- 如果未提供 token，先检查环境变量中是否已保存 `DATAIFY_API_TOKEN`。\n- 如果本地已保存 `DATAIFY_API_TOKEN`，则直接使用。\n- 如果本地没有可用的 token，提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n- 没有 token 不要调用 Builder 接口。\n- 在面向用户的说明中始终称其为 `API TOKEN`。在本地保存使用时，优先使用环境变量名 `DATAIFY_API_TOKEN`。\n\nPowerShell 示例，为当前会话保存 token：\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\n在 Windows 上设置持久的用户级变量：\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## 核心工作流程\n\n3. 询问：\"在我提交任务之前，您是否需要修改这些值？\"\n4. 将最终值规范化为 `keyword`、`domain`、`page_turning` 和 `file_name`。\n5. 从用户明确提供的输入或已保存的 `DATAIFY_API_TOKEN` 中获取 Dataify token。\n6. 如果没有可用的 token，提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n7. 验证必填字段和数值约束。\n8. 提交 Builder 请求创建任务。\n9. 从 Builder 响应中读取 `data.task_id`。\n10. 告诉用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看或管理结果。\n\n## 参数清单\n\n| 字段 | 必填 | 默认值 | 说明 |\n| --- | --- | --- | --- |\n| `keyword` | 是 | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon 产品列表关键词查询。 |\n| `domain` | 是 | `https://www.amazon.com/` | Amazon 域名。 |\n| `page_turning` | 否 | `1` | 采集的页数。必须是大于等于 `0` 的整数。 |\n| `file_name` | 否 | `{{TasksID}}` | Builder 表单字段。可由用户修改。 |\n\n如果用户已经提供了部分值，在表格中显示这些值代替默认值，只询问是否需要修改剩余/使用默认值的参数。\n\n## Dataify Builder 请求\n\n使用表单字段而不是手动构建的 URL 编码字符串。\n\n- URL：`https://scraperapi.dataify.com/builder`\n- 方法：`POST`\n- Authorization 头：`Bearer DATAIFY_API_TOKEN`\n- Content type：`application/x-www-form-urlencoded`\n- 固定字段：\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- 动态字段：\n  - `spider_parameters` 必须是 JSON 字符串，不能是原始对象。\n  - `file_name` 默认为 `{{TasksID}}`，可由用户修改。\n\n## 脚本\n\n为确保稳定执行，建议使用 Python 3.6 或更新版本运行 `scripts/submit_amazon_product_list.py`，而不是重写 Builder 流程。脚本使用 UTF-8 编码进行读写。\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\n脚本会输出包含 `task_id`、`keyword`、`domain`、`page_turning`、`file_name`、`dashboard_url` 和 `message` 的 JSON 摘要。\n\n## 故障排除\n\n`Missing Dataify API TOKEN` 表示没有传入明确的 token 且本地未保存 `DATAIFY_API_TOKEN`。提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n\n`Keyword cannot be empty` 表示没有提供有效的关键词查询。\n\n`Domain cannot be empty` 表示没有提供有效的域名。\n\n`Page turning must be greater than or equal to 0` 表示页数数值无效。\n\n`File name cannot be empty` 表示没有提供有效的 `file_name`。\n\n缺少 `task_id` 通常表示 authorization 头、token、`spider_name` 或 `spider_id` 有误。\n\n## 注意事项\n\n- 不要编造结果字段。\n- 成功创建任务后，始终引导用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill)。\n\n## 参数交互策略\n\n- 当请求意图明确、只读、低风险且成本较低时，使用安全默认值直接执行。可以用一句话说明执行内容，但不要暂停等待确认。\n- 只在缺少必填输入、存在会明显改变结果的歧义、大批量或多页采集、媒体下载、会明显增加积分消耗、不可逆操作，或用户明确要求查看参数时询问。\n- 必须确认时，只展示会影响目标、范围、输出或成本的用户参数。优先使用一句简短说明；只有三个及以上关键值确实需要比较时才使用精简表格。\n- 不要展示固定字段、空的可选字段、未修改的默认值、凭据或内部实现参数，例如引擎选择、响应格式开关、偏移量、spider ID 和文件名模板。\n- 默认隐藏高级筛选项，除非用户主动询问或需要它们消除歧义。不得用文档示例值代替用户缺失的必填输入。\n- 先返回首个结果，再提供相关的细化选项，不要在首次执行前强迫用户决定所有可选项。\n\n## Account CTA policy\n\n- Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.\n- For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.\n- Detect the current operating system and shell. Show only the matching session-scoped setup command first (`export` for macOS/Linux shells, `$env:` for Windows PowerShell, or `set` for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.\n- After the user says the token is configured, verify only whether `DATAIFY_API_TOKEN` is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.\n- Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project `.env` unless the execution path explicitly loads it, and ensure `.env` is ignored by version control.\n- For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.\n- During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.\n\nFile v1.3.0:agents/openai.yaml\n\ninterface:\n  display_name: \"Dataify Amazon Product List\"\n  short_description: \"Collect Amazon Product List data and return results\"\n  default_prompt: \"Use $dataify-amazon-product-list to complete the requested Dataify collection, wait for the asynchronous task, and return the final collected result. Stop at task submission only when I explicitly request no-wait behavior.\"\n\npolicy:\n  allow_implicit_invocation: true\n\nArchive v1.2.0: 6 files, 8269 bytes\n\nFiles: agents/openai.yaml (315b), scripts/submit_amazon_product_list.py (4752b), skill-card.md (2132b), SKILL.md (5284b), SKILL.zh-CN.md (5034b), _meta.json (146b)\n\nFile v1.2.0:SKILL.md\n\n---\nname: dataify-amazon-product-list\ndescription: Use for Dataify Amazon product list collection Builder tasks. Trigger when the user says or asks for Amazon 产品列表采集工具, Amazon product list collection tool, Amazon product list tool, Amazon product list collection, Amazon product list scraping, or Amazon product list keyword collection by keyword and domain. Supports creating an amazon_product-list_by-keywords-domain task; returning the task_id; configuring or reusing the DATAIFY_API_TOKEN environment variable; and troubleshooting Dataify Builder request failures.\n---\n\n# Dataify Amazon Product List\n\nSubmit Amazon product list collection jobs by keyword and domain through Dataify Builder, then stop. After a successful submission, give the user the `task_id` and tell them to visit [Dataify](https://dashboard.dataify.com?utm_source=skill) to view results.\n\n## API TOKEN Handling\n\nUse `DATAIFY_API_TOKEN` as the long-term saved token name.\n\n- If the user provides a token in the request, use it for this run.\n- If no token is provided, first check whether `DATAIFY_API_TOKEN` is already saved locally in the environment.\n- If `DATAIFY_API_TOKEN` is saved locally, use it.\n- If no token is available locally, tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n- Do not call the Builder endpoint without a token.\n- Always call it `API TOKEN` in user-facing instructions. Prefer the environment variable name `DATAIFY_API_TOKEN` for saved local use.\n\nPowerShell examples for saving the token for the current session:\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\nFor a persistent user-level variable on Windows:\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## Core Workflow\n\n1. Before submitting, show the user the required values, optional values, and defaults listed in the Parameter Checklist.\n2. Always display submitted parameters as a Markdown table; do not use a plain sentence or bullet list for parameter confirmation.\n3. Ask: \"Do you want to change any of these values before I submit the task?\"\n4. Normalize the final values into `keyword`, `domain`, `page_turning`, and `file_name`.\n5. Resolve the Dataify token from explicit input or saved `DATAIFY_API_TOKEN`.\n6. If no token is available, tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n7. Validate required fields and numeric constraints.\n8. Submit a Builder request to create the task.\n9. Read `data.task_id` from the Builder response.\n10. Tell the user to visit [Dataify](https://dashboard.dataify.com?utm_source=skill) to view or manage results.\n\n## Parameter Checklist\n\n| Field | Required | Default | Notes |\n| --- | --- | --- | --- |\n| `keyword` | Yes | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon product-list keyword query. |\n| `domain` | Yes | `https://www.amazon.com/` | Amazon domain. |\n| `page_turning` | No | `1` | Number of pages to collect. Must be an integer greater than or equal to `0`. |\n| `file_name` | No | `{{TasksID}}` | Builder form field. Can be changed by the user. |\n\nIf the user has already provided some values, show those values in place of the defaults and only ask whether the remaining/defaulted values should be changed.\n\n## Dataify Builder Request\n\nUse form fields rather than hand-built URL-encoded strings.\n\n- URL: `https://scraperapi.dataify.com/builder`\n- Method: `POST`\n- Authorization header: `Bearer DATAIFY_API_TOKEN`\n- Content type: `application/x-www-form-urlencoded`\n- Fixed fields:\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- Dynamic fields:\n  - `spider_parameters` must be a JSON string, not a raw object.\n  - `file_name` defaults to `{{TasksID}}` and can be changed by the user.\n\n## Script\n\nFor stable execution, prefer `scripts/submit_amazon_product_list.py` with Python 3.6 or newer instead of rewriting the Builder flow. The script writes and reads UTF-8 text.\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\nThe script prints a JSON summary with `task_id`, `keyword`, `domain`, `page_turning`, `file_name`, `dashboard_url`, and `message`.\n\n## Troubleshooting\n\n`Missing Dataify API TOKEN` means no explicit token was passed and `DATAIFY_API_TOKEN` is not saved locally. Tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n\n`Keyword cannot be empty` means no usable keyword query was provided.\n\n`Domain cannot be empty` means no usable domain was provided.\n\n`Page turning must be greater than or equal to 0` means the numeric page count is invalid.\n\n`File name cannot be empty` means no usable `file_name` was provided.\n\nMissing `task_id` usually means the authorization header, token, `spider_name`, or `spider_id` is wrong.\n\n## Guardrails\n\n- Do not invent result fields.\n- Always direct the user to [Dataify](https://dashboard.dataify.com?utm_source=skill) after successful task creation.\n\nFile v1.2.0:_meta.json\n\n{\n  \"ownerId\": \"kn74z5hmmwk21kw8tpphd9w21x86bkdf\",\n  \"slug\": \"dataify-amazon-product-list\",\n  \"version\": \"1.2.0\",\n  \"publishedAt\": 1784190914154\n}\n\nFile v1.2.0:skill-card.md\n\n## Description: <br>\nSubmits Dataify Builder jobs for Amazon product list collection by keyword and domain, returns the task_id, and helps configure DATAIFY_API_TOKEN. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[dataify-server](https://clawhub.ai/user/dataify-server) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to confirm Amazon collection parameters, submit a Dataify Builder task, and retrieve the task_id for later result review in Dataify. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: The skill can use DATAIFY_API_TOKEN from the local environment to submit requests to Dataify. <br>\nMitigation: Use a token intended for Dataify task submission and avoid sharing it in prompts or persisted files. <br>\nRisk: Submitted keywords, domains, page counts, and file names are sent to Dataify. <br>\nMitigation: Review the parameter table before submission and avoid sensitive terms or file names. <br>\nRisk: Incorrect task parameters can submit the wrong Amazon collection job. <br>\nMitigation: Confirm required and optional values before allowing the Builder request. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/dataify-server/skills/dataify-amazon-product-list) <br>\n- [Dataify dashboard](https://dashboard.dataify.com?utm_source=skill) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Markdown, Shell commands, Configuration, JSON, Guidance] <br>\n**Output Format:** [Markdown parameter table, shell commands, and JSON task summary] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Returns task_id and Dataify dashboard URL after successful submission.] <br>\n\n## Skill Version(s): <br>\n1.2.0 (source: server release evidence) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.2.0:SKILL.zh-CN.md\n\n---\nname: dataify-amazon-product-list\ndescription: \"用于 Dataify Amazon 商品列表采集 Builder 任务。当用户说到或请求 Amazon 产品列表采集工具、Amazon product list collection/tool/scraping，或按 keyword and domain 采集 Amazon product list 时触发。支持创建 amazon_product-list_by-keywords-domain 任务、返回 task_id、配置或复用 DATAIFY_API_TOKEN，并排查 Dataify Builder 请求失败。\"\n---\n\n# Dataify Amazon Product List\n\n通过 Dataify Builder 按关键词和域名提交 Amazon 产品列表采集任务，提交后停止。成功提交后，将 `task_id` 提供给用户，并告知他们前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看结果。\n\n## API TOKEN 处理\n\n使用 `DATAIFY_API_TOKEN` 作为长期保存的 token 名称。\n\n- 如果用户在请求中提供了 token，则在本次运行中使用该 token。\n- 如果未提供 token，先检查环境变量中是否已保存 `DATAIFY_API_TOKEN`。\n- 如果本地已保存 `DATAIFY_API_TOKEN`，则直接使用。\n- 如果本地没有可用的 token，提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n- 没有 token 不要调用 Builder 接口。\n- 在面向用户的说明中始终称其为 `API TOKEN`。在本地保存使用时，优先使用环境变量名 `DATAIFY_API_TOKEN`。\n\nPowerShell 示例，为当前会话保存 token：\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\n在 Windows 上设置持久的用户级变量：\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## 核心工作流程\n\n1. 提交前，向用户展示参数清单中列出的必填值、可选值和默认值。\n2. 始终以 Markdown 表格展示已提交的参数；不要使用纯文本句子或项目符号列表进行参数确认。\n3. 询问：\"在我提交任务之前，您是否需要修改这些值？\"\n4. 将最终值规范化为 `keyword`、`domain`、`page_turning` 和 `file_name`。\n5. 从用户明确提供的输入或已保存的 `DATAIFY_API_TOKEN` 中获取 Dataify token。\n6. 如果没有可用的 token，提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n7. 验证必填字段和数值约束。\n8. 提交 Builder 请求创建任务。\n9. 从 Builder 响应中读取 `data.task_id`。\n10. 告诉用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看或管理结果。\n\n## 参数清单\n\n| 字段 | 必填 | 默认值 | 说明 |\n| --- | --- | --- | --- |\n| `keyword` | 是 | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon 产品列表关键词查询。 |\n| `domain` | 是 | `https://www.amazon.com/` | Amazon 域名。 |\n| `page_turning` | 否 | `1` | 采集的页数。必须是大于等于 `0` 的整数。 |\n| `file_name` | 否 | `{{TasksID}}` | Builder 表单字段。可由用户修改。 |\n\n如果用户已经提供了部分值，在表格中显示这些值代替默认值，只询问是否需要修改剩余/使用默认值的参数。\n\n## Dataify Builder 请求\n\n使用表单字段而不是手动构建的 URL 编码字符串。\n\n- URL：`https://scraperapi.dataify.com/builder`\n- 方法：`POST`\n- Authorization 头：`Bearer DATAIFY_API_TOKEN`\n- Content type：`application/x-www-form-urlencoded`\n- 固定字段：\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- 动态字段：\n  - `spider_parameters` 必须是 JSON 字符串，不能是原始对象。\n  - `file_name` 默认为 `{{TasksID}}`，可由用户修改。\n\n## 脚本\n\n为确保稳定执行，建议使用 Python 3.6 或更新版本运行 `scripts/submit_amazon_product_list.py`，而不是重写 Builder 流程。脚本使用 UTF-8 编码进行读写。\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\n脚本会输出包含 `task_id`、`keyword`、`domain`、`page_turning`、`file_name`、`dashboard_url` 和 `message` 的 JSON 摘要。\n\n## 故障排除\n\n`Missing Dataify API TOKEN` 表示没有传入明确的 token 且本地未保存 `DATAIFY_API_TOKEN`。提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n\n`Keyword cannot be empty` 表示没有提供有效的关键词查询。\n\n`Domain cannot be empty` 表示没有提供有效的域名。\n\n`Page turning must be greater than or equal to 0` 表示页数数值无效。\n\n`File name cannot be empty` 表示没有提供有效的 `file_name`。\n\n缺少 `task_id` 通常表示 authorization 头、token、`spider_name` 或 `spider_id` 有误。\n\n## 注意事项\n\n- 不要编造结果字段。\n- 成功创建任务后，始终引导用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill)。\n\nFile v1.2.0:agents/openai.yaml\n\ninterface:\n  display_name: \"Dataify Amazon Product List\"\n  short_description: \"Submit Dataify Amazon product list collection tasks\"\n  default_prompt: \"Use $dataify-amazon-product-list to submit Amazon product list collection tasks through Dataify and return the task_id.\"\n\npolicy:\n  allow_implicit_invocation: true\n\nArchive v1.1.0: 6 files, 8354 bytes\n\nFiles: agents/openai.yaml (315b), scripts/submit_amazon_product_list.py (4752b), skill-card.md (2251b), SKILL.md (5284b), SKILL.zh-CN.md (5034b), _meta.json (146b)\n\nFile v1.1.0:SKILL.md\n\n---\nname: dataify-amazon-product-list\ndescription: Use for Dataify Amazon product list collection Builder tasks. Trigger when the user says or asks for Amazon 产品列表采集工具, Amazon product list collection tool, Amazon product list tool, Amazon product list collection, Amazon product list scraping, or Amazon product list keyword collection by keyword and domain. Supports creating an amazon_product-list_by-keywords-domain task; returning the task_id; configuring or reusing the DATAIFY_API_TOKEN environment variable; and troubleshooting Dataify Builder request failures.\n---\n\n# Dataify Amazon Product List\n\nSubmit Amazon product list collection jobs by keyword and domain through Dataify Builder, then stop. After a successful submission, give the user the `task_id` and tell them to visit [Dataify](https://dashboard.dataify.com?utm_source=skill) to view results.\n\n## API TOKEN Handling\n\nUse `DATAIFY_API_TOKEN` as the long-term saved token name.\n\n- If the user provides a token in the request, use it for this run.\n- If no token is provided, first check whether `DATAIFY_API_TOKEN` is already saved locally in the environment.\n- If `DATAIFY_API_TOKEN` is saved locally, use it.\n- If no token is available locally, tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n- Do not call the Builder endpoint without a token.\n- Always call it `API TOKEN` in user-facing instructions. Prefer the environment variable name `DATAIFY_API_TOKEN` for saved local use.\n\nPowerShell examples for saving the token for the current session:\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\nFor a persistent user-level variable on Windows:\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## Core Workflow\n\n1. Before submitting, show the user the required values, optional values, and defaults listed in the Parameter Checklist.\n2. Always display submitted parameters as a Markdown table; do not use a plain sentence or bullet list for parameter confirmation.\n3. Ask: \"Do you want to change any of these values before I submit the task?\"\n4. Normalize the final values into `keyword`, `domain`, `page_turning`, and `file_name`.\n5. Resolve the Dataify token from explicit input or saved `DATAIFY_API_TOKEN`.\n6. If no token is available, tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n7. Validate required fields and numeric constraints.\n8. Submit a Builder request to create the task.\n9. Read `data.task_id` from the Builder response.\n10. Tell the user to visit [Dataify](https://dashboard.dataify.com?utm_source=skill) to view or manage results.\n\n## Parameter Checklist\n\n| Field | Required | Default | Notes |\n| --- | --- | --- | --- |\n| `keyword` | Yes | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon product-list keyword query. |\n| `domain` | Yes | `https://www.amazon.com/` | Amazon domain. |\n| `page_turning` | No | `1` | Number of pages to collect. Must be an integer greater than or equal to `0`. |\n| `file_name` | No | `{{TasksID}}` | Builder form field. Can be changed by the user. |\n\nIf the user has already provided some values, show those values in place of the defaults and only ask whether the remaining/defaulted values should be changed.\n\n## Dataify Builder Request\n\nUse form fields rather than hand-built URL-encoded strings.\n\n- URL: `https://scraperapi.dataify.com/builder`\n- Method: `POST`\n- Authorization header: `Bearer DATAIFY_API_TOKEN`\n- Content type: `application/x-www-form-urlencoded`\n- Fixed fields:\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- Dynamic fields:\n  - `spider_parameters` must be a JSON string, not a raw object.\n  - `file_name` defaults to `{{TasksID}}` and can be changed by the user.\n\n## Script\n\nFor stable execution, prefer `scripts/submit_amazon_product_list.py` with Python 3.6 or newer instead of rewriting the Builder flow. The script writes and reads UTF-8 text.\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\nThe script prints a JSON summary with `task_id`, `keyword`, `domain`, `page_turning`, `file_name`, `dashboard_url`, and `message`.\n\n## Troubleshooting\n\n`Missing Dataify API TOKEN` means no explicit token was passed and `DATAIFY_API_TOKEN` is not saved locally. Tell the user to get an API TOKEN from [Dataify](https://dashboard.dataify.com?utm_source=skill).\n\n`Keyword cannot be empty` means no usable keyword query was provided.\n\n`Domain cannot be empty` means no usable domain was provided.\n\n`Page turning must be greater than or equal to 0` means the numeric page count is invalid.\n\n`File name cannot be empty` means no usable `file_name` was provided.\n\nMissing `task_id` usually means the authorization header, token, `spider_name`, or `spider_id` is wrong.\n\n## Guardrails\n\n- Do not invent result fields.\n- Always direct the user to [Dataify](https://dashboard.dataify.com?utm_source=skill) after successful task creation.\n\nFile v1.1.0:_meta.json\n\n{\n  \"ownerId\": \"kn74z5hmmwk21kw8tpphd9w21x86bkdf\",\n  \"slug\": \"dataify-amazon-product-list\",\n  \"version\": \"1.1.0\",\n  \"publishedAt\": 1780884327197\n}\n\nFile v1.1.0:skill-card.md\n\n## Description: <br>\nSubmits Amazon product list collection jobs by keyword and domain through Dataify Builder and returns the resulting task ID. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[dataify-server](https://clawhub.ai/user/dataify-server) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to create Dataify Builder jobs for Amazon product list collection, confirm submission parameters, and retrieve the task_id for later result management in Dataify. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: The skill uses a long-lived Dataify API TOKEN and sends submitted keyword, domain, page count, and file-name values to Dataify Builder. <br>\nMitigation: Confirm the submission parameters before running, avoid private or sensitive business queries unless appropriate, and store DATAIFY_API_TOKEN only in an approved local environment. <br>\nRisk: A missing or invalid token, incorrect Builder identifiers, or invalid input values can cause the submission to fail or return no task_id. <br>\nMitigation: Validate required fields and page count, use the provided script where possible, and surface Builder errors without inventing result fields. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/dataify-server/dataify-amazon-product-list) <br>\n- [Dataify dashboard](https://dashboard.dataify.com?utm_source=skill) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Text, Markdown, Shell commands, Configuration, API calls, JSON] <br>\n**Output Format:** [Markdown guidance with parameter tables, shell commands, and JSON task summaries] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Returns task_id, submitted parameter values, dashboard_url, and status or troubleshooting messages.] <br>\n\n## Skill Version(s): <br>\n1.1.0 (source: server release evidence) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.1.0:SKILL.zh-CN.md\n\n---\nname: dataify-amazon-product-list\ndescription: \"用于 Dataify Amazon 商品列表采集 Builder 任务。当用户说到或请求 Amazon 产品列表采集工具、Amazon product list collection/tool/scraping，或按 keyword and domain 采集 Amazon product list 时触发。支持创建 amazon_product-list_by-keywords-domain 任务、返回 task_id、配置或复用 DATAIFY_API_TOKEN，并排查 Dataify Builder 请求失败。\"\n---\n\n# Dataify Amazon Product List\n\n通过 Dataify Builder 按关键词和域名提交 Amazon 产品列表采集任务，提交后停止。成功提交后，将 `task_id` 提供给用户，并告知他们前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看结果。\n\n## API TOKEN 处理\n\n使用 `DATAIFY_API_TOKEN` 作为长期保存的 token 名称。\n\n- 如果用户在请求中提供了 token，则在本次运行中使用该 token。\n- 如果未提供 token，先检查环境变量中是否已保存 `DATAIFY_API_TOKEN`。\n- 如果本地已保存 `DATAIFY_API_TOKEN`，则直接使用。\n- 如果本地没有可用的 token，提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n- 没有 token 不要调用 Builder 接口。\n- 在面向用户的说明中始终称其为 `API TOKEN`。在本地保存使用时，优先使用环境变量名 `DATAIFY_API_TOKEN`。\n\nPowerShell 示例，为当前会话保存 token：\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\n在 Windows 上设置持久的用户级变量：\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## 核心工作流程\n\n1. 提交前，向用户展示参数清单中列出的必填值、可选值和默认值。\n2. 始终以 Markdown 表格展示已提交的参数；不要使用纯文本句子或项目符号列表进行参数确认。\n3. 询问：\"在我提交任务之前，您是否需要修改这些值？\"\n4. 将最终值规范化为 `keyword`、`domain`、`page_turning` 和 `file_name`。\n5. 从用户明确提供的输入或已保存的 `DATAIFY_API_TOKEN` 中获取 Dataify token。\n6. 如果没有可用的 token，提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n7. 验证必填字段和数值约束。\n8. 提交 Builder 请求创建任务。\n9. 从 Builder 响应中读取 `data.task_id`。\n10. 告诉用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看或管理结果。\n\n## 参数清单\n\n| 字段 | 必填 | 默认值 | 说明 |\n| --- | --- | --- | --- |\n| `keyword` | 是 | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon 产品列表关键词查询。 |\n| `domain` | 是 | `https://www.amazon.com/` | Amazon 域名。 |\n| `page_turning` | 否 | `1` | 采集的页数。必须是大于等于 `0` 的整数。 |\n| `file_name` | 否 | `{{TasksID}}` | Builder 表单字段。可由用户修改。 |\n\n如果用户已经提供了部分值，在表格中显示这些值代替默认值，只询问是否需要修改剩余/使用默认值的参数。\n\n## Dataify Builder 请求\n\n使用表单字段而不是手动构建的 URL 编码字符串。\n\n- URL：`https://scraperapi.dataify.com/builder`\n- 方法：`POST`\n- Authorization 头：`Bearer DATAIFY_API_TOKEN`\n- Content type：`application/x-www-form-urlencoded`\n- 固定字段：\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- 动态字段：\n  - `spider_parameters` 必须是 JSON 字符串，不能是原始对象。\n  - `file_name` 默认为 `{{TasksID}}`，可由用户修改。\n\n## 脚本\n\n为确保稳定执行，建议使用 Python 3.6 或更新版本运行 `scripts/submit_amazon_product_list.py`，而不是重写 Builder 流程。脚本使用 UTF-8 编码进行读写。\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\n脚本会输出包含 `task_id`、`keyword`、`domain`、`page_turning`、`file_name`、`dashboard_url` 和 `message` 的 JSON 摘要。\n\n## 故障排除\n\n`Missing Dataify API TOKEN` 表示没有传入明确的 token 且本地未保存 `DATAIFY_API_TOKEN`。提示用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 获取 API TOKEN。\n\n`Keyword cannot be empty` 表示没有提供有效的关键词查询。\n\n`Domain cannot be empty` 表示没有提供有效的域名。\n\n`Page turning must be greater than or equal to 0` 表示页数数值无效。\n\n`File name cannot be empty` 表示没有提供有效的 `file_name`。\n\n缺少 `task_id` 通常表示 authorization 头、token、`spider_name` 或 `spider_id` 有误。\n\n## 注意事项\n\n- 不要编造结果字段。\n- 成功创建任务后，始终引导用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill)。\n\nFile v1.1.0:agents/openai.yaml\n\ninterface:\n  display_name: \"Dataify Amazon Product List\"\n  short_description: \"Submit Dataify Amazon product list collection tasks\"\n  default_prompt: \"Use $dataify-amazon-product-list to submit Amazon product list collection tasks through Dataify and return the task_id.\"\n\npolicy:\n  allow_implicit_invocation: true\n\nArchive v1.0.0: 5 files, 5744 bytes\n\nFiles: agents/openai.yaml (315b), scripts/submit_amazon_product_list.py (4709b), skill-card.md (2070b), SKILL.md (5128b), _meta.json (146b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: dataify-amazon-product-list\ndescription: Use for Dataify Amazon product list collection Builder tasks. Trigger when the user says or asks for Amazon 产品列表采集工具, Amazon product list collection tool, Amazon product list tool, Amazon product list collection, Amazon product list scraping, or Amazon product list keyword collection by keyword and domain. Supports creating an amazon_product-list_by-keywords-domain task; returning the task_id; configuring or reusing the DATAIFY_API_TOKEN environment variable; and troubleshooting Dataify Builder request failures.\n---\n\n# Dataify Amazon Product List\n\nSubmit Amazon product list collection jobs by keyword and domain through Dataify Builder, then stop. After a successful submission, give the user the `task_id` and tell them to visit `https://dataify.com/dashboard/` to view results.\n\n## API TOKEN Handling\n\nUse `DATAIFY_API_TOKEN` as the long-term saved token name.\n\n- If the user provides a token in the request, use it for this run.\n- If no token is provided, first check whether `DATAIFY_API_TOKEN` is already saved locally in the environment.\n- If `DATAIFY_API_TOKEN` is saved locally, use it.\n- If no token is available locally, tell the user to get an API TOKEN from [Dataify](https://dataify.com).\n- Do not call the Builder endpoint without a token.\n- Always call it `API TOKEN` in user-facing instructions. Prefer the environment variable name `DATAIFY_API_TOKEN` for saved local use.\n\nPowerShell examples for saving the token for the current session:\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\nFor a persistent user-level variable on Windows:\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## Core Workflow\n\n1. Before submitting, show the user the required values, optional values, and defaults listed in the Parameter Checklist.\n2. Always display submitted parameters as a Markdown table; do not use a plain sentence or bullet list for parameter confirmation.\n3. Ask: \"Do you want to change any of these values before I submit the task?\"\n4. Normalize the final values into `keyword`, `domain`, `page_turning`, and `file_name`.\n5. Resolve the Dataify token from explicit input or saved `DATAIFY_API_TOKEN`.\n6. If no token is available, tell the user to get an API TOKEN from [Dataify](https://dataify.com).\n7. Validate required fields and numeric constraints.\n8. Submit a Builder request to create the task.\n9. Read `data.task_id` from the Builder response.\n10. Tell the user to visit `https://dataify.com/dashboard/` to view or manage results.\n\n## Parameter Checklist\n\n| Field | Required | Default | Notes |\n| --- | --- | --- | --- |\n| `keyword` | Yes | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon product-list keyword query. |\n| `domain` | Yes | `https://www.amazon.com/` | Amazon domain. |\n| `page_turning` | No | `1` | Number of pages to collect. Must be an integer greater than or equal to `0`. |\n| `file_name` | No | `{{TasksID}}` | Builder form field. Can be changed by the user. |\n\nIf the user has already provided some values, show those values in place of the defaults and only ask whether the remaining/defaulted values should be changed.\n\n## Dataify Builder Request\n\nUse form fields rather than hand-built URL-encoded strings.\n\n- URL: `https://scraperapi.dataify.com/builder`\n- Method: `POST`\n- Authorization header: `Bearer DATAIFY_API_TOKEN`\n- Content type: `application/x-www-form-urlencoded`\n- Fixed fields:\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- Dynamic fields:\n  - `spider_parameters` must be a JSON string, not a raw object.\n  - `file_name` defaults to `{{TasksID}}` and can be changed by the user.\n\n## Script\n\nFor stable execution, prefer `scripts/submit_amazon_product_list.py` with Python 3.6 or newer instead of rewriting the Builder flow. The script writes and reads UTF-8 text.\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\nThe script prints a JSON summary with `task_id`, `keyword`, `domain`, `page_turning`, `file_name`, `dashboard_url`, and `message`.\n\n## Troubleshooting\n\n`Missing Dataify API TOKEN` means no explicit token was passed and `DATAIFY_API_TOKEN` is not saved locally. Tell the user to get an API TOKEN from [Dataify](https://dataify.com).\n\n`Keyword cannot be empty` means no usable keyword query was provided.\n\n`Domain cannot be empty` means no usable domain was provided.\n\n`Page turning must be greater than or equal to 0` means the numeric page count is invalid.\n\n`File name cannot be empty` means no usable `file_name` was provided.\n\nMissing `task_id` usually means the authorization header, token, `spider_name`, or `spider_id` is wrong.\n\n## Guardrails\n\n- Do not invent result fields.\n- Always direct the user to `https://dataify.com/dashboard/` after successful task creation.\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn74z5hmmwk21kw8tpphd9w21x86bkdf\",\n  \"slug\": \"dataify-amazon-product-list\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1779949863571\n}\n\nFile v1.0.0:skill-card.md\n\n## Description: <br>\nSubmits Amazon product list collection jobs by keyword and domain through Dataify Builder and returns the Dataify task ID. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[dataify-server](https://clawhub.ai/user/dataify-server) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to submit Dataify Builder tasks for Amazon product-list collection, confirm the collection parameters, and receive the resulting task ID for follow-up in the Dataify dashboard. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: The skill uses a Dataify API TOKEN to submit Builder requests. <br>\nMitigation: Treat DATAIFY_API_TOKEN as a secret and prefer session-scoped or protected storage. <br>\nRisk: The skill creates remote Dataify Amazon collection tasks using user-supplied or default parameters. <br>\nMitigation: Review the displayed keyword, domain, page count, and file name before allowing submission. <br>\n\n\n## Reference(s): <br>\n- [ClawHub Skill Page](https://clawhub.ai/dataify-server/dataify-amazon-product-list) <br>\n- [Dataify](https://dataify.com) <br>\n- [Dataify Dashboard](https://dataify.com/dashboard/) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Text, Markdown, Shell commands, Configuration, API calls] <br>\n**Output Format:** [Markdown parameter confirmation with JSON task summary from the helper script] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Requires a Dataify API TOKEN; submits a remote Builder task and returns task_id, keyword, domain, page_turning, file_name, dashboard_url, and message.] <br>\n\n## Skill Version(s): <br>\n1.0.0 (source: server release metadata) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.0.0:agents/openai.yaml\n\ninterface:\n  display_name: \"Dataify Amazon Product List\"\n  short_description: \"Submit Dataify Amazon product list collection tasks\"\n  default_prompt: \"Use $dataify-amazon-product-list to submit Amazon product list collection tasks through Dataify and return the task_id.\"\n\npolicy:\n  allow_implicit_invocation: true","readmeExcerpt":"Skill: Dataify Amazon Product List Owner: dataify-server Summary: Collect Amazon Product List data and return results Tags: latest:1.3.1 Version history: v1.3.1 | 2026-09-08T06:17:38.744Z | user Fix natural-language usage failures: validate required targets and URLs, preserve catalog references, default Amazon region safely, normalize Google News links, and improve UTF-8 error output. v1.3.0 | 2026-09-01T09:12:13.070","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"python3 scripts/submit_amazon_product_list.py --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1"},{"language":"powershell","snippet":"$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\""},{"language":"powershell","snippet":"[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")"},{"language":"powershell","snippet":"python3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\""},{"language":"powershell","snippet":"$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\""},{"language":"powershell","snippet":"[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: dataify-amazon-product-list\ndescription: \"Collect Amazon product-list records by keyword and marketplace domain. Use when both list-style results and a target Amazon domain are required. Do not use for a single ASIN, product details, reviews, or global brand collection.\"\n---\n\n# Dataify Amazon Product List\n\nSubmit Amazon product list collection jobs by keyword and domain through Dataify Builder and continue through final-result retrieval. After submission, continue monitoring the returned `task_id` and return the final result by default.\n\n\n## Quick Start\n\n**Input:** a keyword and Amazon domain.\n\n```bash\npython3 scripts/submit_amazon_product_list.py --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1\n```\n\nThe command waits up to 10 minutes and prints the final JSON result. Add `--no-wait` only for submission-only behavior.\n\nIf `DATAIFY_API_TOKEN` is missing, log in or register at https://dashboard.dataify.com/login?utm_source=skill. New accounts get 50 free credits, enough for about 6,000 trial results, valid for 7 days, and only successful requests are billed.\n\n## API TOKEN Handling\n\nUse `DATAIFY_API_TOKEN` as the long-term saved token name.\n\n- If `DATAIFY_API_TOKEN` is saved locally, use it.\n- Do not call the Builder endpoint without a token.\n- Always call it `API TOKEN` in user-facing instructions. Prefer the environment variable name `DATAIFY_API_TOKEN` for saved local use.\n\nPowerShell examples for saving the token for the current session:\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\nFor a persistent user-level variable on Windows:\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## Core Workflow\n\n3. Ask: \"Do you want to change any of these values before I submit the task?\"\n4. Normalize the final values into `keyword`, `domain`, `page_turning`, and `file_name`.\n7. Validate required fields and numeric constraints.\n8. Submit a Builder request to create the task.\n9. Read `data.task_id` from the Builder response.\n\n## Parameter Checklist\n\n| Field | Required | Default | Notes |\n| --- | --- | --- | --- |\n| `keyword` | Yes | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon product-list keyword query. |\n| `domain` | Yes | `https://www.amazon.com/` | Amazon domain. |\n| `page_turning` | No | `1` | Number of pages to collect. Must be an integer greater than or equal to `0`. |\n| `file_name` | No | `{{TasksID}}` | Builder form field. Can be changed by the user. |\n\nIf the user has already provided some values, show those values in place of the defaults and only ask whether the remaining/defaulted values should be changed.\n\n## Dataify Builder Request\n\nUse form fields rather than hand-built URL-encoded strings.\n\n- URL: `https://scraperapi.dataify.com/builder`\n- Method: `POST`\n- Authorization header: `Bearer DATAIFY_API_TOKEN`\n- Content type: `application/x-www-form-urlenc"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn74z5hmmwk21kw8tpphd9w21x86bkdf\",\n  \"slug\": \"dataify-amazon-product-list\",\n  \"version\": \"1.3.1\",\n  \"publishedAt\": 1788848258744\n}"},{"path":"skill-card.md","content":"## Description:\n\nCollect Amazon product-list records by keyword and marketplace domain through Dataify Builder and return the collected JSON result.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[dataify-server](https://clawhub.ai/user/dataify-server)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and operators use this skill to submit Dataify Amazon product-list collection jobs by keyword and Amazon marketplace domain, then monitor the task and retrieve final JSON results. It is intended for list-style Amazon collection, not single-ASIN details, reviews, or global brand collection.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill requires a Dataify account token and can submit paid or credit-consuming Dataify jobs.\n\nMitigation: Configure DATAIFY_API_TOKEN through the local environment, do not expose token values in chat or logs, and confirm high-volume or multi-page collection scopes before execution.\n\nRisk: Security evidence reports credential and import-handling risks, including token-in-query and external import-path behavior.\n\nMitigation: Review, fix, or explicitly accept these behaviors before installation; run the skill in a least-privileged environment until resolved.\n\nRisk: Security evidence reports broader under-disclosed scraping and business-intelligence helper code beyond the advertised Amazon-list workflow.\n\nMitigation: Review the bundled scripts before deployment and restrict invocation to the advertised Amazon product-list workflow unless the additional helpers are intentionally approved.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/dataify-server/skills/dataify-amazon-product-list)\n- [Dataify dashboard](https://dashboard.dataify.com?utm_source=skill)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]\n\n**Output Format:** [Markdown guidance with shell commands and JSON task/result output]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires DATAIFY_API_TOKEN; normal execution can submit credit-consuming Dataify jobs and may wait for asynchronous task completion.]\n\n## Skill Version(s):\n\n1.3.1 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."},{"path":"SKILL.zh-CN.md","content":"---\nname: dataify-amazon-product-list\ndescription: \"用于 Dataify Amazon 商品列表采集 Builder 任务。当用户说到或请求 Amazon 产品列表采集工具、Amazon product list collection/tool/scraping，或按 keyword and domain 采集 Amazon product list 时触发。支持创建 amazon_product-list_by-keywords-domain 任务、返回 task_id、配置或复用 DATAIFY_API_TOKEN，并排查 Dataify Builder 请求失败。\"\n---\n\n# Dataify Amazon Product List\n\n通过 Dataify Builder 按关键词和域名提交 Amazon 产品列表采集任务，提交后停止。成功提交后，将 `task_id` 提供给用户，并告知他们前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看结果。\n\n## API TOKEN 处理\n\n使用 `DATAIFY_API_TOKEN` 作为长期保存的 token 名称。\n\n- 如果用户在请求中提供了 token，则在本次运行中使用该 token。\n- 如果未提供 token，先检查环境变量中是否已保存 `DATAIFY_API_TOKEN`。\n- 如果本地已保存 `DATAIFY_API_TOKEN`，则直接使用。\n- 如果本地没有可用的 token，告诉用户：`Dataify 需要 API Token。新账号注册即得 50 免费积分，约可获得 6000 条试用结果，7 天有效，仅成功请求计费。注册完成后告诉我，我会继续当前任务。`。\n- 没有 token 不要调用 Builder 接口。\n- 在面向用户的说明中始终称其为 `API TOKEN`。在本地保存使用时，优先使用环境变量名 `DATAIFY_API_TOKEN`。\n\nPowerShell 示例，为当前会话保存 token：\n\n```powershell\n$env:DATAIFY_API_TOKEN = \"YOUR_DATAIFY_API_TOKEN\"\n```\n\n在 Windows 上设置持久的用户级变量：\n\n```powershell\n[Environment]::SetEnvironmentVariable(\"DATAIFY_API_TOKEN\", \"YOUR_DATAIFY_API_TOKEN\", \"User\")\n```\n\n## 核心工作流程\n\n3. 询问：\"在我提交任务之前，您是否需要修改这些值？\"\n4. 将最终值规范化为 `keyword`、`domain`、`page_turning` 和 `file_name`。\n5. 从用户明确提供的输入或已保存的 `DATAIFY_API_TOKEN` 中获取 Dataify token。\n6. 如果没有可用的 token，告诉用户：`Dataify 需要 API Token。新账号注册即得 50 免费积分，约可获得 6000 条试用结果，7 天有效，仅成功请求计费。注册完成后告诉我，我会继续当前任务。`。\n7. 验证必填字段和数值约束。\n8. 提交 Builder 请求创建任务。\n9. 从 Builder 响应中读取 `data.task_id`。\n10. 告诉用户前往 [Dataify](https://dashboard.dataify.com?utm_source=skill) 查看或管理结果。\n\n## 参数清单\n\n| 字段 | 必填 | 默认值 | 说明 |\n| --- | --- | --- | --- |\n| `keyword` | 是 | `https://www.amazon.com/sp?ie=UTF8&seller=ADZ7LD48GVFQJ&asin=B07H56J7K1&ref_=dp_merchant_link&isAmazonFulfilled=1` | Amazon 产品列表关键词查询。 |\n| `domain` | 是 | `https://www.amazon.com/` | Amazon 域名。 |\n| `page_turning` | 否 | `1` | 采集的页数。必须是大于等于 `0` 的整数。 |\n| `file_name` | 否 | `{{TasksID}}` | Builder 表单字段。可由用户修改。 |\n\n如果用户已经提供了部分值，在表格中显示这些值代替默认值，只询问是否需要修改剩余/使用默认值的参数。\n\n## Dataify Builder 请求\n\n使用表单字段而不是手动构建的 URL 编码字符串。\n\n- URL：`https://scraperapi.dataify.com/builder`\n- 方法：`POST`\n- Authorization 头：`Bearer DATAIFY_API_TOKEN`\n- Content type：`application/x-www-form-urlencoded`\n- 固定字段：\n  - `spider_name=amazon.com`\n  - `spider_id=amazon_product-list_by-keywords-domain`\n  - `spider_errors=true`\n- 动态字段：\n  - `spider_parameters` 必须是 JSON 字符串，不能是原始对象。\n  - `file_name` 默认为 `{{TasksID}}`，可由用户修改。\n\n## 脚本\n\n为确保稳定执行，建议使用 Python 3.6 或更新版本运行 `scripts/submit_amazon_product_list.py`，而不是重写 Builder 流程。脚本使用 UTF-8 编码进行读写。\n\n```powershell\npython3 \".\\scripts\\submit_amazon_product_list.py\"\npython3 \".\\scripts\\submit_amazon_product_list.py\" --keyword \"coffee\" --domain \"https://www.amazon.com/\" --page-turning 1 --file-name \"amazon-product-list\"\n```\n\n脚本会输出包含 `task_id`、`keyword`、`domain`、`page_turning`、`file_name`、`dashboard_url` 和 `message` 的 JSON 摘要。\n\n## 故障排除\n\n`Missing Dataify API TOKEN` 表示没有传入明确的 token 且本地未保存 `DATAIFY_API_TOKEN`。告诉用户：`Dataify 需要 API Token。新账号注册即得 50 免费积分，约可获得 6000 条试用结果，7 天有效，仅成功请求计"},{"path":"agents/openai.yaml","content":"interface:\n  display_name: \"Dataify Amazon Product List\"\n  short_description: \"Collect Amazon Product List data and return results\"\n  default_prompt: \"Use $dataify-amazon-product-list to complete the requested Dataify collection, wait for the asynchronous task, and return the final collected result. 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