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document-review文件审查

Agent Skill

document-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

397

周安装

17

GitHub Stars

16,238

下载量

140
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:document-review(文件审查)
来源仓库:https://github.com/udecode/plate
仓库路径:skills/document-review
安装命令:
npx skills add https://github.com/udecode/plate --skill document-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/udecode/plate --skill document-review

简介

document-review 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中基于关键词快速定位候选结果。
  • 通过 npx skills add 命令从 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件操作。
  • 建议结合原始 README 进一步验证功能细节。

SKILL.md

Document Review

Review requirements or plan documents through multi-persona analysis. Dispatches specialized reviewer agents in parallel, auto-fixes quality issues, and presents strategic questions for user decision.

Phase 1: Get and Analyze Document

If a document path is provided: Read it, then proceed.

If no document is specified: Ask which document to review, or find the most recent in docs/brainstorms/ or docs/plans/ using a file-search/glob tool (e.g., Glob in Claude Code).

Classify Document Type

After reading, classify the document:

  • requirements -- from docs/brainstorms/, focuses on what to build and why
  • plan -- from docs/plans/, focuses on how to build it with implementation details

Select Conditional Personas

Analyze the document content to determine which conditional personas to activate. Check for these signals:

product-lens -- activate when the document contains:

  • User-facing features, user stories, or customer-focused language
  • Market claims, competitive positioning, or business justification
  • Scope decisions, prioritization language, or priority tiers with feature assignments
  • Requirements with user/customer/business outcome focus

design-lens -- activate when the document contains:

  • UI/UX references, frontend components, or visual design language
  • User flows, wireframes, screen/page/view mentions
  • Interaction descriptions (forms, buttons, navigation, modals)
  • References to responsive behavior or accessibility

security-lens -- activate when the document contains:

  • Auth/authorization mentions, login flows, session management
  • API endpoints exposed to external clients
  • Data handling, PII, payments, tokens, credentials, encryption
  • Third-party integrations with trust boundary implications

scope-guardian -- activate when the document contains:

  • Multiple priority tiers (P0/P1/P2, must-have/should-have/nice-to-have)
  • Large requirement count (>8 distinct requirements or implementation units)
  • Stretch goals, nice-to-haves, or "future work" sections
  • Scope boundary language that seems misaligned with stated goals
  • Goals that don't clearly connect to requirements

adversarial -- activate when the document contains:

  • More than 5 distinct requirements or implementation units
  • Explicit architectural or scope decisions with stated rationale
  • High-stakes domains (auth, payments, data migrations, external integrations)
  • Proposals of new abstractions, frameworks, or significant architectural patterns

Phase 2: Announce and Dispatch Personas

Announce the Review Team

Tell the user which personas will review and why. For conditional personas, include the justification:

Reviewing with:
- coherence-reviewer (always-on)
- feasibility-reviewer (always-on)
- scope-guardian-reviewer -- plan has 12 requirements across 3 priority levels
- security-lens-reviewer -- plan adds API endpoints with auth flow

Build Agent List

Always include:

  • compound-engineering:document-review:coherence-reviewer
  • compound-engineering:document-review:feasibility-reviewer

Add activated conditional personas:

  • compound-engineering:document-review:product-lens-reviewer
  • compound-engineering:document-review:design-lens-reviewer
  • compound-engineering:document-review:security-lens-reviewer
  • compound-engineering:document-review:scope-guardian-reviewer
  • compound-engineering:document-review:adversarial-document-reviewer

Dispatch

Dispatch all agents in parallel using the platform's task/agent tool (e.g., Agent tool in Claude Code, spawn in Codex). Each agent receives the prompt built from the subagent template included below with these variables filled:

VariableValue
{persona_file}Full content of the agent's markdown file
{schema}Content of the findings schema included below
{document_type}"requirements" or "plan" from Phase 1 classification
{document_path}Path to the document
{document_content}Full text of the document

Pass each agent the full document -- do not split into sections.

Error handling: If an agent fails or times out, proceed with findings from agents that completed. Note the failed agent in the Coverage section. Do not block the entire review on a single agent failure.

Dispatch limit: Even at maximum (7 agents), use parallel dispatch. These are document reviewers with bounded scope reading a single document -- parallel is safe and fast.

Phase 3: Synthesize Findings

Process findings from all agents through this pipeline. Order matters -- each step depends on the previous.

3.1 Validate

Check each agent's returned JSON against the findings schema included below:

  • Drop findings missing any required field defined in the schema
  • Drop findings with invalid enum values
  • Note the agent name for any malformed output in the Coverage section

3.2 Confidence Gate

Suppress findings below 0.50 confidence. Store them as residual concerns for potential promotion in step 3.4.

3.3 Deduplicate

Fingerprint each finding using normalize(section) + normalize(title). Normalization: lowercase, strip punctuation, collapse whitespace.

When fingerprints match across personas:

  • If the findings recommend opposing actions (e.g., one says cut, the other says keep), do not merge -- preserve both for contradiction resolution in 3.5
  • Otherwise merge: keep the highest severity, keep the highest confidence, union all evidence arrays, note all agreeing reviewers (e.g., "coherence, feasibility")

3.4 Promote Residual Concerns

Scan the residual concerns (findings suppressed in 3.2) for:

  • Cross-persona corroboration: A residual concern from Persona A overlaps with an above-threshold finding from Persona B. Promote at P2 with confidence 0.55-0.65. Inherit finding_type from the corroborating above-threshold finding.
  • Concrete blocking risks: A residual concern describes a specific, concrete risk that would block implementation. Promote at P2 with confidence 0.55. Set finding_type: omission (blocking risks surfaced as residual concerns are inherently about something the document failed to address).

3.5 Resolve Contradictions

When personas disagree on the same section:

  • Create a combined finding presenting both perspectives
  • Set autofix_class: present
  • Set finding_type: error (contradictions are by definition about conflicting things the document says, not things it omits)
  • Frame as a tradeoff, not a verdict

Specific conflict patterns:

  • Coherence says "keep for consistency" + scope-guardian says "cut for simplicity" -> combined finding, let user decide
  • Feasibility says "this is impossible" + product-lens says "this is essential" -> P1 finding framed as a tradeoff
  • Multiple personas flag the same issue -> merge into single finding, note consensus, increase confidence

3.6 Route by Autofix Class

Autofix ClassRoute
autoApply automatically -- local deterministic fix (terminology, formatting, cross-references, completeness corrections where the correct value is verifiable from the document itself)
batch_confirmGroup for single batch approval -- obvious fixes that touch meaning but have one clear correct answer
presentPresent individually for user judgment

Demote any auto finding that lacks a suggested_fix to batch_confirm. Demote any batch_confirm finding that lacks a suggested_fix to present.

Completeness corrections eligible for auto: A finding qualifies when the correct fix is deterministically derivable from other content in the document. Examples: a count says "6 units" but the document lists 7, a summary omits an item that appears in the detailed list, a cross-reference points to a renamed section. If the fix requires judgment about *what* to add (not just *that* something is missing), it belongs in batch_confirm or present.

3.7 Sort

Sort findings for presentation: P0 -> P1 -> P2 -> P3, then by finding type (errors before omissions), then by confidence (descending), then by document order (section position).

Phase 4: Apply and Present

Apply Auto-fixes

Apply all auto findings to the document in a single pass:

  • Edit the document inline using the platform's edit tool
  • Track what was changed for the "Auto-fixes Applied" section
  • Do not ask for approval -- these are unambiguously correct

Batch Confirm

If any batch_confirm findings exist, present them as a group for a single approval:

  • List the proposed fixes in a numbered table
  • Use the platform's blocking question tool (AskUserQuestion in Claude Code, request_user_input in Codex, ask_user in Gemini) to ask: "Apply these N fixes? (yes/no/select)". If no blocking question tool is available, present the table with numbered options and wait for the user's reply before proceeding.
  • If approved, apply all in a single pass
  • If "select", let the user pick which to apply
  • If rejected, demote remaining to the present findings list

This turns N obvious-but-meaning-touching fixes into 1 interaction instead of N.

Present Remaining Findings

Present present findings using the review output template included below. Within each severity level, separate findings by type:

  • Errors (design tensions, contradictions, incorrect statements) first -- these need resolution
  • Omissions (missing steps, absent details, forgotten entries) second -- these need additions

Brief summary at the top: "Applied N auto-fixes. Batched M fixes for approval. K findings to consider (X errors, Y omissions)."

Include the Coverage table, auto-fixes applied, residual concerns, and deferred questions.

Protected Artifacts

During synthesis, discard any finding that recommends deleting or removing files in:

  • docs/brainstorms/
  • docs/plans/
  • docs/solutions/

These are pipeline artifacts and must not be flagged for removal.

Phase 5: Next Action

Use the platform's blocking question tool when available (AskUserQuestion in Claude Code, request_user_input in Codex, ask_user in Gemini). Otherwise present numbered options and wait for the user's reply.

Offer:

  1. Refine again -- another review pass
  2. Review complete -- document is ready

After 2 refinement passes, recommend completion -- diminishing returns are likely. But if the user wants to continue, allow it.

Return "Review complete" as the terminal signal for callers.

What NOT to Do

  • Do not rewrite the entire document
  • Do not add new sections or requirements the user didn't discuss
  • Do not over-engineer or add complexity
  • Do not create separate review files or add metadata sections
  • Do not modify any of the 2 caller skills (ce-brainstorm, ce-plan)

Iteration Guidance

On subsequent passes, re-dispatch personas and re-synthesize. The auto-fix mechanism and confidence gating prevent the same findings from recurring once fixed. If findings are repetitive across passes, recommend completion.


Included References

Subagent Template

@./references/subagent-template.md

Findings Schema

@./references/findings-schema.json

Review Output Template

@./references/review-output-template.md

适合场景

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.07%
按下载量换算50

Claude

29.85%
按下载量换算42

Cursor

16.85%
按下载量换算24

Gemini CLI

9.52%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/udecode/plate --skill document-review 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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