{"id":"030bda4b-6311-4fa0-b3ed-3caf5c85da7b","entityType":"agent","slug":"crewai-sketchrrr-official-doc-insight","name":"official-doc-insight","canonicalUrl":"https://www.xpersona.co/agent/crewai-sketchrrr-official-doc-insight","canonicalPath":"/agent/crewai-sketchrrr-official-doc-insight","generatedAt":"2026-10-10T07:02:48.884Z","source":"GITHUB_REPOS","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T17:06:05.301Z","emptyReason":null},"description":"A multi-agent pipeline built with CrewAI that deconstructs official documents—discourse analysis, sentiment profiling, and subtext mining—and produces decision-ready Markdown insight reports. 基于 CrewAI 的多智能体流水线，对官方发文做话语拆解、情绪画像、潜台词挖掘，并输出可支撑决策的 Markdown 洞察报告。 官方发文深度解读系统 / Official Document Insight Crew $1 | $1 --- 中文 基于 $1 的多智能体流水线，对官方发文做话语拆解、情绪画像、潜台词挖掘，并输出可支撑决策的 Markdown 洞察报告。 架构 **4 Agents + 4 Sequential Tasks**（顺序执行，后序任务可引用前序结果）： | Agent | 职责 | | --- | --- | | 话语体系解码专家 | 拆解高频词、新增/罕见表述、缺席惯用语、弹性措辞 | | 情绪与风向感知专家 | 整体基调 + 五维度评分 + 对各主体态度 | | 战略情报挖掘分析师 | 推断未明说事实，强制附原文依据与置信度 | | 决策参考报告主笔 | 整合前三步，输出分级结论与后续观察建议 | 设计原则： - 专家优于通才（Specialists over Generalists） - 单一目标任务（Single Purp","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 10/9/2026.","installCommand":null,"sourceUrl":"https://github.com/sketchrrr/official-doc-insight","homepage":null,"primaryLinks":[{"label":"View Source","url":"https://github.com/sketchrrr/official-doc-insight","kind":"source"}],"safetyScore":66,"overallRank":20.8,"popularityScore":8,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"A multi-agent pipeline built with CrewAI that deconstructs official documents—discourse analysis, sentiment profiling, and subtext mining—and produces decision-"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-09T17:06:05.301Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[{"label":"crewai","status":"self-declared"},{"label":"multi-agent","status":"self-declared"}],"verifiedCount":0,"selfDeclaredCount":3,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"},{"key":"crewai","type":"capability","support":"supported","confidenceSource":"profile","notes":"Declared in agent profile metadata"},{"key":"multi-agent","type":"capability","support":"supported","confidenceSource":"profile","notes":"Declared in agent profile metadata"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"}},"adoption":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"medium","updatedAt":"2026-10-09T17:06:05.301Z","emptyReason":null},"stars":1,"forks":0,"downloads":null,"packageName":null,"latestVersion":null,"tractionLabel":"1 GitHub stars"},"release":{"evidence":{"source":"agent-index","verified":false,"confidence":"medium","updatedAt":"2026-10-09T17:06:05.295Z","emptyReason":null},"lastUpdatedAt":"2026-10-09T17:06:05.301Z","lastCrawledAt":"2026-10-09T17:06:05.295Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-16T17:06:05.295Z","lastVerifiedAt":null,"highlights":[]},"execution":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":null,"setupComplexity":"low","setupSteps":["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/crewai-sketchrrr-official-doc-insight/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"GITHUB_REPOS","generatedAt":"2026-10-10T07:02:48.884Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-sketchrrr-official-doc-insight/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is 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":"GITHUB REPOS","verified":false,"confidence":"high","updatedAt":"2026-10-09T17:06:05.301Z","emptyReason":null},"readme":"# 官方发文深度解读系统 / Official Document Insight Crew\n\n[中文](#中文) | [English](#english)\n\n---\n\n## 中文\n\n基于 [CrewAI](https://www.crewai.com/) 的多智能体流水线，对官方发文做话语拆解、情绪画像、潜台词挖掘，并输出可支撑决策的 Markdown 洞察报告。\n\n### 架构\n\n**4 Agents + 4 Sequential Tasks**（顺序执行，后序任务可引用前序结果）：\n\n| Agent | 职责 |\n| --- | --- |\n| 话语体系解码专家 | 拆解高频词、新增/罕见表述、缺席惯用语、弹性措辞 |\n| 情绪与风向感知专家 | 整体基调 + 五维度评分 + 对各主体态度 |\n| 战略情报挖掘分析师 | 推断未明说事实，强制附原文依据与置信度 |\n| 决策参考报告主笔 | 整合前三步，输出分级结论与后续观察建议 |\n\n设计原则：\n\n- 专家优于通才（Specialists over Generalists）\n- 单一目标任务（Single Purpose, Single Output）\n- 强制原文引用，防止过度解读（Anti-Hallucination）\n\n### 环境要求\n\n- Python >= 3.11\n- [OpenRouter](https://openrouter.ai/) API Key\n\n### 快速开始\n\n#### 1. 安装依赖\n\n推荐使用 [uv](https://github.com/astral-sh/uv)：\n\n```bash\nuv sync\n```\n\n或使用 pip：\n\n```bash\npip install -e .\n```\n\n#### 2. 配置环境变量\n\n复制示例文件并填入密钥：\n\n```bash\ncp .env.example .env\n```\n\n| 变量 | 说明 |\n| --- | --- |\n| `OPENROUTER_API_KEY` | 必填，在 [OpenRouter Keys](https://openrouter.ai/keys) 创建 |\n| `OPENROUTER_MODEL` | 可选，默认 `openrouter/openai/gpt-4o`；格式为 `openrouter/<provider>/<model>` |\n\n#### 3. 运行\n\n```bash\nuv run python main.py\n```\n\n或：\n\n```bash\npython main.py\n```\n\n### 输入格式\n\n程序会提示一次性粘贴全部内容，另起一行输入 `END` 结束。\n\n**仅发文：**\n\n```text\n（粘贴官方发文全文）\nEND\n```\n\n**带背景信息：**\n\n```text\n（背景说明，如发文时间、发布机构、关联政策等）\n---\n（粘贴官方发文全文）\nEND\n```\n\n背景与正文之间用单独一行的 `---` 分隔；无背景时可直接粘贴发文。\n\n### 输出\n\n- 终端打印最终 Markdown 报告\n- 同时写入当前目录下的 `result.md`\n\n报告结构大致为：\n\n1. 核心结论\n2. 官方态度与情绪画像\n3. 话语体系关键信号\n4. 暗藏的事实与推论（分置信度）\n5. 后续观察建议\n\n历史样例可参考 `result/` 目录。\n\n### 项目结构\n\n```text\nofficial-doc-insight/\n├── main.py          # Crew / Agent / Task 定义与入口\n├── pyproject.toml   # 依赖与项目元数据\n├── .env.example     # 环境变量模板\n├── result/          # 历史解读样例（可选）\n└── README.md\n```\n\n---\n\n## English\n\nA multi-agent pipeline built with [CrewAI](https://www.crewai.com/) that deconstructs official documents—discourse analysis, sentiment profiling, and subtext mining—and produces decision-ready Markdown insight reports.\n\n### Architecture\n\n**4 Agents + 4 Sequential Tasks** (run in order; later tasks can reference earlier outputs):\n\n| Agent | Responsibility |\n| --- | --- |\n| Discourse System Decoder | Extract high-frequency terms, new/rare phrasing, absent stock phrases, and elastic wording |\n| Sentiment & Trend Sensor | Overall tone + five-dimension scores + attitudes toward each subject |\n| Strategic Intelligence Analyst | Infer unspoken facts, with mandatory source quotes and confidence levels |\n| Decision Brief Lead Writer | Synthesize the first three steps into tiered conclusions and follow-up watchpoints |\n\nDesign principles:\n\n- Specialists over Generalists\n- Single Purpose, Single Output\n- Mandatory source citations to reduce over-interpretation (Anti-Hallucination)\n\n### Requirements\n\n- Python >= 3.11\n- [OpenRouter](https://openrouter.ai/) API Key\n\n### Quick Start\n\n#### 1. Install dependencies\n\nRecommended: [uv](https://github.com/astral-sh/uv):\n\n```bash\nuv sync\n```\n\nOr with pip:\n\n```bash\npip install -e .\n```\n\n#### 2. Configure environment variables\n\nCopy the example file and fill in your keys:\n\n```bash\ncp .env.example .env\n```\n\n| Variable | Description |\n| --- | --- |\n| `OPENROUTER_API_KEY` | Required. Create one at [OpenRouter Keys](https://openrouter.ai/keys) |\n| `OPENROUTER_MODEL` | Optional. Default `openrouter/openai/gpt-4o`; format `openrouter/<provider>/<model>` |\n\n#### 3. Run\n\n```bash\nuv run python main.py\n```\n\nOr:\n\n```bash\npython main.py\n```\n\n### Input Format\n\nThe program prompts you to paste all content at once, then type `END` on a new line to finish.\n\n**Document only:**\n\n```text\n(paste the full official document)\nEND\n```\n\n**With background context:**\n\n```text\n(background notes, e.g. publish date, issuing body, related policies)\n---\n(paste the full official document)\nEND\n```\n\nSeparate background and body with a single-line `---`. If there is no background, paste the document directly.\n\n### Output\n\n- Prints the final Markdown report to the terminal\n- Also writes `result.md` in the current directory\n\nTypical report structure:\n\n1. Core conclusions\n2. Official stance and sentiment profile\n3. Key discourse signals\n4. Hidden facts and inferences (by confidence)\n5. Follow-up observation suggestions\n\nSee the `result/` directory for historical samples.\n\n### Project Structure\n\n```text\nofficial-doc-insight/\n├── main.py          # Crew / Agent / Task definitions and entrypoint\n├── pyproject.toml   # Dependencies and project metadata\n├── .env.example     # Environment variable template\n├── result/          # Historical interpretation samples (optional)\n└── README.md\n```\n","readmeExcerpt":"官方发文深度解读系统 / Official Document Insight Crew $1 | $1 --- 中文 基于 $1 的多智能体流水线，对官方发文做话语拆解、情绪画像、潜台词挖掘，并输出可支撑决策的 Markdown 洞察报告。 架构 **4 Agents + 4 Sequential Tasks**（顺序执行，后序任务可引用前序结果）： | Agent | 职责 | | --- | --- | | 话语体系解码专家 | 拆解高频词、新增/罕见表述、缺席惯用语、弹性措辞 | | 情绪与风向感知专家 | 整体基调 + 五维度评分 + 对各主体态度 | | 战略情报挖掘分析师 | 推断未明说事实，强制附原文依据与置信度 | | 决策参考报告主笔 | 整合前三步，输出分级结论与后续观察建议 | 设计原则： - 专家优于通才（Specialists over Generalists） - 单一目标任务（Single Purp","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"uv sync"},{"language":"bash","snippet":"pip install -e ."},{"language":"bash","snippet":"cp .env.example .env"},{"language":"bash","snippet":"uv run python main.py"},{"language":"bash","snippet":"python main.py"},{"language":"text","snippet":"（粘贴官方发文全文）\nEND"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["python"],"docsSourceLabel":"GITHUB REPOS","editorialOverview":"A multi-agent pipeline built with CrewAI that deconstructs official documents—discourse analysis, sentiment profiling, and subtext mining—and produces decision-ready Markdown insight reports. 基于 CrewAI 的多智能体流水线，对官方发文做话语拆解、情绪画像、潜台词挖掘，并输出可支撑决策的 Markdown 洞察报告。 官方发文深度解读系统 / Official Document Insight Crew $1 | $1 --- 中文 基于 $1 的多智能体流水线，对官方发文做话语拆解、情绪画像、潜台词挖掘，并输出可支撑决策的 Markdown 洞察报告。 架构 **4 Agents + 4 Sequential Tasks**（顺序执行，后序任务可引用前序结果）： | Agent | 职责 | | --- | --- | | 话语体系解码专家 | 拆解高频词、新增/罕见表述、缺席惯用语、弹性措辞 | | 情绪与风向感知专家 | 整体基调 + 五维度评分 + 对各主体态度 | | 战略情报挖掘分析师 | 推断未明说事实，强制附原文依据与置信度 | | 决策参考报告主笔 | 整合前三步，输出分级结论与后续观察建议 | 设计原则： - 专家优于通才（Specialists over Generalists） - 单一目标任务（Single Purp","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":354,"uniquenessScore":67,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-09T17:06:05.301Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-09T17:06:05.301Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T07:02:48.884Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs","url":"https://github.com/CherryHQ/cherry-studio","homepage":"https://cherry-ai.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-11T14:38:40.986Z","createdAt":"2026-02-25T03:38:19.379Z","downloads":null},{"id":"6f6582d0-5d76-4f0f-b81d-86520247950b","entityType":"agent","canonicalPath":"/agent/copilotkit-copilotkit","slug":"copilotkit-copilotkit","name":"CopilotKit","description":"The Frontend for Agents & Generative UI. React + Angular","url":"https://github.com/CopilotKit/CopilotKit","homepage":"https://docs.copilotkit.ai","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-03-25T09:50:57.846Z","createdAt":"2026-02-25T03:39:14.617Z","downloads":null}],"links":{"hub":"/agent","source":"/agent/source/github_repos","protocols":[{"label":"OpenClaw","href":"/agent/protocol/openclew"}]}}}