據 AlphaMoat 統計,截至 2026-09,Claude 累計下載 3,201 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,556 位,在「專業領域」分類(465 個)中排名第 287 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 57 | 2007 | - | - |
| SkillHub ↗ | 161 | 3201 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
擷取文件核心邏輯、假設、矛盾、歧義和風險,可將材料摘要、比較、診斷或改寫為面向決策的格式。區分事實、推論與建議,並保留重要細節和不確定性。不替代執業法律意見,也不代替法務、稅務、法令遵循、採購或合約正式審批。 提供文件或片段、審閱目的、所支持決策、讀者及分析模式,標出未解決假設和不確定性;分析不產生事實或批准權限。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。 該技能有同名的其他版本,調整前的資料歸屬當前下載量最大的這一個。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3201 | — | 1 |
| 2026-08 | 2141 | +20.4% | 1 |
| 2026-07 | 1778 | +18.7% | 1 |
| 2026-06 | 1498 | +18.1% | 1 |
| 2026-05 | 1268 | — | 1 |
| 2026-03 | 691 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 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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資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。