据 AlphaMoat 统计,截至 2026-09,Claude 累计下载 3,201 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 3,556 位,在「专业领域」分类(465 个)中排名第 287 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 57 | 2,007 | - | - |
| SkillHub ↗ | 161 | 3,201 | 1 | — |
各平台的计数口径不同,统计时间不一致。
提取文档核心逻辑、假设、矛盾、歧义和风险,可将材料总结、比较、诊断或改写为面向决策的格式。区分事实、推断与建议,并保留重要细节和不确定性。不替代执业法律意见,也不代替法务、税务、合规、采购或合同正式审批。 提供文档或片段、审阅目的、所支持决策、读者及分析模式,标出未解决假设和不确定性;分析不产生事实或批准权限。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。 该技能有同名的其他版本,调整前的数据归属当前下载量最大的这一个。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,201 | — | 1 |
| 2026-08 | 2,141 | +20.4% | 1 |
| 2026-07 | 1,778 | +18.7% | 1 |
| 2026-06 | 1,498 | +18.1% | 1 |
| 2026-05 | 1,268 | — | 1 |
| 2026-03 | 691 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: Claude description: > Optimize long-context reasoning for commercial, legal, and high-stakes documents. Built for users who need stronger logic, cleaner structure, and deeper analysis across contracts, memos, negotiations, and complex written materials. version: 1.0.0 --- # Claude
> **Turn long, messy, high-stakes documents into sharper reasoning and cleaner decisions.** Claude is a long-context reasoning optimizer for commercial and legal document workflows. Use this skill when you need to: - analyze long contracts, memos, proposals, or negotiations - improve reasoning quality across dense written material - surface contradictions, weak logic, or missing assumptions - compress large documents into decision-ready summaries - strengthen document structure before review or approval - compare multiple versions of a long-form document This skill does NOT: - replace licensed legal advice - guarantee correctness in regulated or high-risk matters - sign off on legal, tax, or compliance decisions - act as a substitute for professional counsel --- ## What This Skill Does Claude helps: - extract the core logic from long documents - identify missing assumptions and weak reasoning - clarify structure, argument flow, and decision relevance - detect inconsistencies, ambiguity, and hidden risk - improve summaries without losing critical nuance - rewrite dense content into cleaner, more usable formats --- ## Best Use Cases - contract review preparation - commercial memo analysis - proposal and redline review - policy comparison - negotiation brief preparation - board or executive memo compression - legal-adjacent document structuring --- ## What to Provide Useful input includes: - the full document or excerpt - the purpose of the review - the decision being supported - known risks or pressure points - the audience for the final output - whether you want diagnosis, summary, rewrite, or comparison --- ## Standard Output Format DOCUMENT ASSESSMENT ━━━━━━━━━━━━━━━━━━━━━━━━━━ Purpose: [What this document is trying to do] Audience: [Who the output is for] Decision relevance: [Why this matters] CORE LOGIC ━━━━━━━━━━━━━━━━━━━━━━━━━━ - [Main claim / obligation / commercial point] - [Supporting logic] - [Critical assumption] RISKS / WEAK POINTS ━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ [Ambiguity] ⚠️ [Contradiction] ⚠️ [Missing assumption] ⚠️ [Commercial or legal risk signal] STRUCTURE IMPROVEMENTS ━━━━━━━━━━━━━━━━━━━━━━━━━━ 1. [How to make reasoning clearer] 2. [How to reduce ambiguity] 3. [How to improve decision usefulness] RECOMMENDED NEXT STEP ━━━━━━━━━━━━━━━━━━━━━━━━━━ - [Review further / rewrite / compare versions / escalate to counsel / prepare summary] --- ## Reasoning Principles - preserve critical nuance - do not compress away risk - separate fact, inference, and recommendation - identify what is explicit vs implied - highlight missing assumptions before proposing conclusions - prefer clarity over flourish - never invent legal or commercial certainty --- ## Execution Protocol (for AI agents) When user provides a long document, follow this sequence: ### Step 1: Parse context Extract: - document type - intended audience - decision being supported - major obligations, claims, or asks - commercial or legal sensitivity ### Step 2: Identify logic structure Map: - what the document is saying - why it matters - what assumptions it depends on - what could fail under scrutiny ### Step 3: Detect weaknesses Check for: - ambiguity - contradiction - undefined terms - missing scope boundaries - missing decision logic - hidden risk transfer - structural confusion ### Step 4: Improve usefulness Depending on request: - summarize - rewrite - compare - diagnose - convert into brief / memo / checklist ### Step 5: Guardrails If legal or commercial certainty cannot be established from the text: - say so clearly - mark uncertainty - do not fabricate confidence --- ## Activation Rules (for AI agents) ### Use this skill when the user asks about: - long documents - contract-like text - legal-adjacent review - memo analysis - commercial document reasoning - dense text summarization with nuance - comparing two long versions of a document ### Do NOT use this skill when: - user only needs a casual short rewrite - user needs creative writing instead of reasoning - user needs formal legal advice or sign-off - user asks for certainty where the text does not support it ### If context is ambiguous Ask: "Do you want deep reasoning and document analysis, or just a simple rewrite?" --- ## Works Well With - `@ethagent/review` for narrower document review workflows - `@ethagent/draft` for rewriting after diagnosis - `@dpetcr/proposal` for commercial proposal refinement --- ## Boundaries This skill supports reasoning, structuring, and analysis of long commercial and legal-adjacent documents. It does not replace: - licensed legal advice - contract execution authority - procurement approval - tax or compliance judgment Use outputs as analytical support, not formal sign-off.
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数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。