{"id":"1bbd0c6b-2d0d-4c3d-bf7d-e8ede6e1005e","entityType":"agent","slug":"clawhub-xby-skill-ocr","name":"文本识别OCR","canonicalUrl":"https://www.xpersona.co/agent/clawhub-xby-skill-ocr","canonicalPath":"/agent/clawhub-xby-skill-ocr","generatedAt":"2026-10-11T10:50:14.619Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-11T07:01:40.460Z","emptyReason":null},"description":"兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Skill: 文本识别OCR Owner: xby-skill Summary: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-07-06T09:23:47.738Z | auto 文本识别OCR v1.0.0 - 新增图像文字识别功能，兼顾速度与精度，支持多种场景（文档、广告牌、截图等）。 - 支持通过图片文件链接或Base64编码输入图像。 - 强制要求配置API密钥，缺失时自动向用户询问。 - 明确工具调用和参数提取流程，提升使用便捷性和安全性。 Archive index: Archive v1.0.0: 8 files, 6843 bytes Files: requirements.txt (78b), scripts/__init__.py (0b), sc","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.","installCommand":"clawhub skill install s173mpn8gcwhe5sh4qmweth8e988w95a:ocr","sourceUrl":"https://clawhub.ai/xby-skill/ocr","homepage":"https://clawhub.ai/xby-skill/skills/ocr","primaryLinks":[{"label":"View on ClawHub","url":"https://clawhub.ai/xby-skill/ocr","kind":"source"},{"label":"Homepage","url":"https://clawhub.ai/xby-skill/skills/ocr","kind":"homepage"}],"safetyScore":84,"overallRank":62,"popularityScore":61,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Skill: 文本识别OCR Owner: xby-skill Summary: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Tags: lates"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-11T07:01:40.460Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[],"verifiedCount":0,"selfDeclaredCount":1,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile"}},"adoption":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T07:01:40.460Z","emptyReason":null},"stars":null,"forks":null,"downloads":1128,"packageName":null,"latestVersion":"1.0.0","tractionLabel":"1.1K downloads"},"release":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T07:01:40.399Z","emptyReason":null},"lastUpdatedAt":"2026-10-11T07:01:40.460Z","lastCrawledAt":"2026-10-11T07:01:40.399Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-12T07:01:40.399Z","lastVerifiedAt":null,"highlights":[{"version":"1.0.0","createdAt":"2026-07-06T09:23:47.738Z","changelog":"文本识别OCR v1.0.0 - 新增图像文字识别功能，兼顾速度与精度，支持多种场景（文档、广告牌、截图等）。 - 支持通过图片文件链接或Base64编码输入图像。 - 强制要求配置API密钥，缺失时自动向用户询问。 - 明确工具调用和参数提取流程，提升使用便捷性和安全性。","fileCount":8,"zipByteSize":6843}]},"execution":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"clawhub skill install s173mpn8gcwhe5sh4qmweth8e988w95a:ocr","setupComplexity":"medium","setupSteps":["Python environment detected. Create a strict virtual environment (`python -m venv .venv`) before installing dependencies to prevent system-level package conflicts.","Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/clawhub-xby-skill-ocr/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-xby-skill-ocr/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-xby-skill-ocr/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-xby-skill-ocr/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-xby-skill-ocr/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-xby-skill-ocr/trust\""],"jsonRequestTemplate":{"query":"summarize this 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available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic 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":"high","updatedAt":"2026-10-11T07:01:40.460Z","emptyReason":null},"readme":"Skill: 文本识别OCR\n\nOwner: xby-skill\n\nSummary: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\n\nTags: latest:1.0.0\n\nVersion history:\n\nv1.0.0 | 2026-07-06T09:23:47.738Z | auto\n\n文本识别OCR v1.0.0\n\n- 新增图像文字识别功能，兼顾速度与精度，支持多种场景（文档、广告牌、截图等）。\n- 支持通过图片文件链接或Base64编码输入图像。\n- 强制要求配置API密钥，缺失时自动向用户询问。\n- 明确工具调用和参数提取流程，提升使用便捷性和安全性。\n\nArchive index:\n\nArchive v1.0.0: 8 files, 6843 bytes\n\nFiles: requirements.txt (78b), scripts/__init__.py (0b), scripts/call_api.py (3477b), scripts/config.py (2657b), scripts/tools.py (1122b), skill-card.md (1855b), SKILL.md (4055b), _meta.json (122b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: 文本识别OCR\ndescription: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\nversion: 1.0.0\n---\n\n# 文本识别OCR\n\n兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\n\n---\n\n## ⚠️ 强制要求：API 密钥\n\n**此 Skill 必须配置 API 密钥才能使用。**\n\n- 首次使用时，如果 `.env` 中没有 `XBY_APIKEY`，**必须使用 AskUserQuestion 工具向用户询问 API 密钥**\n- 拿到用户提供的密钥后，调用 `scripts.config.set_api_key(api_key)` 保存，然后继续处理\n- 获取 API 密钥：https://xiaobenyang.com\n- **禁止**在缺少 API 密钥时自行搜索或编造数据\n\n---\n\n## 工作流程（必须遵守）\n\n你（大模型）是路由层，负责理解用户意图、选择工具、提取参数。代码只负责调用API。\n\n```\n用户输入 → 你选择工具 → 提取该工具需要的参数 → 调用 scripts.tools 中的函数 → 返回结果给用户\n```\n\n### 步骤\n\n1. **检查 API 密钥**：如果 `scripts.config.settings.api_key` 为空，使用 AskUserQuestion 询问用户，拿到后调用 `scripts.config.set_api_key(key)` 保存\n2. **选择工具**：根据用户意图从下方工具列表中选择对应的工具函数\n3. **提取参数**：根据选中的工具，提取该工具需要的参数\n4. **调用工具**：使用**关键字参数**调用 `scripts.tools` 中的函数，例如 `scripts.tools.search_schools(score='520', province='北京', category='综合')`\n5. **返回结果**：将工具返回的 `raw` 数据整理后展示给用户\n\n---\n## 工具选择规则\n\n根据用户意图选择对应的工具函数：\n\n| 用户意图 | 工具函数 | \n|---------|---------|\n| 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件链接。 | `scripts.tools.ocr` |\n| 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件的BASE64编码。 | `scripts.tools.ocr_for_data_base64` |\n\n**如果参数不完整，使用 AskUserQuestion 向用户询问缺失的参数。**\n\n---\n\n## 工具函数说明\n\n---\n\n## scripts.tools.ocr\n工具描述：兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件链接。\n### 参数定义\n|参数名称|参数类型|是否必填|默认值|描述|\n|------|-------|------|-----|----|\n|dataUrl|string|true| |图片文件链接地址|\n\n---\n\n## scripts.tools.ocr_for_data_base64\n工具描述：兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件的BASE64编码。\n### 参数定义\n|参数名称|参数类型|是否必填|默认值|描述|\n|------|-------|------|-----|----|\n|dataBase64|string|true| |base64 encoded data of image file|\n\n---\n\n\n---\n\n## 返回值处理\n\n工具函数返回 `dict` 对象：\n- `result[\"raw\"]` - API 原始返回数据（JSON），**直接将此数据整理后展示给用户**\n- `result[\"success\"]` - 是否成功（True/False）\n- `result[\"message\"]` - 状态消息\n\n---\n\n## 项目结构\n\n```\nxiaobenyang_gaokao_skill/\n├── scripts/\n│   ├── __init__.py\n│   ├── config.py       # 配置管理 + set_api_key()\n│   ├── call_api.py      # API 客户端 + call_api()\n│   └── tools.py         # 工具函数（直接调用）\n├── requirements.txt\n└── SKILL.md\n```\n\n---\n\n## 注意事项\n\n1. **API 密钥是必需的**，无密钥时必须通过 AskUserQuestion 询问用户\n2. **禁止**在缺少 API 密钥时自行搜索或编造数据\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn75raw6p9acdmyrzv48w6s3ss88xbca\",\n  \"slug\": \"ocr\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1783329827738\n}\n\nFile v1.0.0:skill-card.md\n\n## Description:\n\n兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[xby-skill](https://clawhub.ai/user/xby-skill)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and developers can use this skill to send image URLs or base64-encoded images for OCR and receive extracted text for documents, screenshots, signs, and similar image-based text sources.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Images or base64 image data are sent to XiaoBenYang's remote API for OCR processing.\n\nMitigation: Use the skill only when remote processing is acceptable, and avoid sensitive documents unless the workspace owner has approved that data flow.\n\nRisk: The skill asks for an API key and stores it in a local .env file in plaintext.\n\nMitigation: Use a trusted workspace, avoid sharing the project directory or .env file, and rotate the API key if the workspace may have been exposed.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/xby-skill/skills/ocr)\n- [XiaoBenYang](https://xiaobenyang.com)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Guidance]\n\n**Output Format:** [Markdown or plain text summary of OCR results]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [The tool response includes success status, raw OCR data, and a status message.]\n\n## Skill Version(s):\n\n1.0.0 (source: frontmatter and 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 v1.0.0:requirements.txt\n\nrequests>=2.31.0\npydantic>=2.7.0\npydantic-settings>=2.2.0\npython-dotenv>=1.0.1","readmeExcerpt":"Skill: 文本识别OCR Owner: xby-skill Summary: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-07-06T09:23:47.738Z | auto 文本识别OCR v1.0.0 - 新增图像文字识别功能，兼顾速度与精度，支持多种场景（文档、广告牌、截图等）。 - 支持通过图片文件链接或Base64编码输入图像。 - 强制要求配置API密钥，缺失时自动向用户询问。 - 明确工具调用和参数提取流程，提升使用便捷性和安全性。 Archive index: Archive v1.0.0: 8 files, 6843 bytes Files: requirements.txt (78b), scripts/__init__.py (0b), sc","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"用户输入 → 你选择工具 → 提取该工具需要的参数 → 调用 scripts.tools 中的函数 → 返回结果给用户"},{"language":"text","snippet":"xiaobenyang_gaokao_skill/\n├── scripts/\n│   ├── __init__.py\n│   ├── config.py       # 配置管理 + set_api_key()\n│   ├── call_api.py      # API 客户端 + call_api()\n│   └── tools.py         # 工具函数（直接调用）\n├── requirements.txt\n└── SKILL.md"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: 文本识别OCR\ndescription: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\nversion: 1.0.0\n---\n\n# 文本识别OCR\n\n兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\n\n---\n\n## ⚠️ 强制要求：API 密钥\n\n**此 Skill 必须配置 API 密钥才能使用。**\n\n- 首次使用时，如果 `.env` 中没有 `XBY_APIKEY`，**必须使用 AskUserQuestion 工具向用户询问 API 密钥**\n- 拿到用户提供的密钥后，调用 `scripts.config.set_api_key(api_key)` 保存，然后继续处理\n- 获取 API 密钥：https://xiaobenyang.com\n- **禁止**在缺少 API 密钥时自行搜索或编造数据\n\n---\n\n## 工作流程（必须遵守）\n\n你（大模型）是路由层，负责理解用户意图、选择工具、提取参数。代码只负责调用API。\n\n```\n用户输入 → 你选择工具 → 提取该工具需要的参数 → 调用 scripts.tools 中的函数 → 返回结果给用户\n```\n\n### 步骤\n\n1. **检查 API 密钥**：如果 `scripts.config.settings.api_key` 为空，使用 AskUserQuestion 询问用户，拿到后调用 `scripts.config.set_api_key(key)` 保存\n2. **选择工具**：根据用户意图从下方工具列表中选择对应的工具函数\n3. **提取参数**：根据选中的工具，提取该工具需要的参数\n4. **调用工具**：使用**关键字参数**调用 `scripts.tools` 中的函数，例如 `scripts.tools.search_schools(score='520', province='北京', category='综合')`\n5. **返回结果**：将工具返回的 `raw` 数据整理后展示给用户\n\n---\n## 工具选择规则\n\n根据用户意图选择对应的工具函数：\n\n| 用户意图 | 工具函数 | \n|---------|---------|\n| 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件链接。 | `scripts.tools.ocr` |\n| 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件的BASE64编码。 | `scripts.tools.ocr_for_data_base64` |\n\n**如果参数不完整，使用 AskUserQuestion 向用户询问缺失的参数。**\n\n---\n\n## 工具函数说明\n\n---\n\n## scripts.tools.ocr\n工具描述：兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件链接。\n### 参数定义\n|参数名称|参数类型|是否必填|默认值|描述|\n|------|-------|------|-----|----|\n|dataUrl|string|true| |图片文件链接地址|\n\n---\n\n## scripts.tools.ocr_for_data_base64\n工具描述：兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 需要输入图片文件的BASE64编码。\n### 参数定义\n|参数名称|参数类型|是否必填|默认值|描述|\n|------|-------|------|-----|----|\n|dataBase64|string|true| |base64 encoded data of image file|\n\n---\n\n\n---\n\n## 返回值处理\n\n工具函数返回 `dict` 对象：\n- `result[\"raw\"]` - API 原始返回数据（JSON），**直接将此数据整理后展示给用户**\n- `result[\"success\"]` - 是否成功（True/False）\n- `result[\"message\"]` - 状态消息\n\n---\n\n## 项目结构\n\n```\nxiaobenyang_gaokao_skill/\n├── scripts/\n│   ├── __init__.py\n│   ├── config.py       # 配置管理 + set_api_key()\n│   ├── call_api.py      # API 客户端 + call_api()\n│   └── tools.py         # 工具函数（直接调用）\n├── requirements.txt\n└── SKILL.md\n```\n\n---\n\n## 注意事项\n\n1. **API 密钥是必需的**，无密钥时必须通过 AskUserQuestion 询问用户\n2. **禁止**在缺少 API 密钥时自行搜索或编造数据"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn75raw6p9acdmyrzv48w6s3ss88xbca\",\n  \"slug\": \"ocr\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1783329827738\n}"},{"path":"skill-card.md","content":"## Description:\n\n兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[xby-skill](https://clawhub.ai/user/xby-skill)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and developers can use this skill to send image URLs or base64-encoded images for OCR and receive extracted text for documents, screenshots, signs, and similar image-based text sources.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Images or base64 image data are sent to XiaoBenYang's remote API for OCR processing.\n\nMitigation: Use the skill only when remote processing is acceptable, and avoid sensitive documents unless the workspace owner has approved that data flow.\n\nRisk: The skill asks for an API key and stores it in a local .env file in plaintext.\n\nMitigation: Use a trusted workspace, avoid sharing the project directory or .env file, and rotate the API key if the workspace may have been exposed.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/xby-skill/skills/ocr)\n- [XiaoBenYang](https://xiaobenyang.com)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Guidance]\n\n**Output Format:** [Markdown or plain text summary of OCR results]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [The tool response includes success status, raw OCR data, and a status message.]\n\n## Skill Version(s):\n\n1.0.0 (source: frontmatter and 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."},{"path":"requirements.txt","content":"requests>=2.31.0\npydantic>=2.7.0\npydantic-settings>=2.2.0\npython-dotenv>=1.0.1"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Skill: 文本识别OCR Owner: xby-skill Summary: 兼顾速度与精度的文字识别。输入包含文本的图像，自动检测并识别内容。适用于各类文档、广告牌、屏幕截图等场景。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-07-06T09:23:47.738Z | auto 文本识别OCR v1.0.0 - 新增图像文字识别功能，兼顾速度与精度，支持多种场景（文档、广告牌、截图等）。 - 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