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Agent Skill · 研究检索

document-review(文件审查)

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。

document-review 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 54,403。

总安装 512周安装 22GitHub Stars 12,713下载 180核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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/everyinc/every-marketplace
仓库路径:skills/document-review
安装命令:
npx skills add https://github.com/everyinc/every-marketplace --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/everyinc/every-marketplace --skill document-review

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

document-review 用于多角色并行评审需求文档,自动修复质量问题并抛出战略疑问。它支持 headless 模式用于 CI/CD 流水线集成,输出结构化反馈。适用于产品需求、技术方案等高价值文档的质量把控。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等操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/document-review

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/everyinc/every-marketplace --skill document-re…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

document-review 怎么安装?

在终端执行 npx skills add https://github.com/everyinc/every-marketplace --skill document-review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

document-review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

document-review 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/everyinc/every-marketplace --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。

document-review 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

document-review 用的人多吗?

公开数据是累计安装 512 次,近一周安装 22 次,下载 180 次,GitHub 12,713 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

document-review 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 12,713 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
document-review

文件审查 · 本页

51212,713执行命令未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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 0: Detect Mode

Check the skill arguments for mode:headless. Arguments may contain a document path, mode:headless, or both. Tokens starting with mode: are flags, not file paths -- strip them from the arguments and use the remaining token (if any) as the document path for Phase 1.

If mode:headless is present, set headless mode for the rest of the workflow.

Headless mode changes the interaction model, not the classification boundaries. Document-review still applies the same judgment about what has one clear correct fix vs. what needs user judgment. The only difference is how non-auto findings are delivered:

  • auto fixes are applied silently (same as interactive)
  • present findings are returned as structured text for the caller to handle -- no AskUserQuestion prompts, no interactive approval
  • Phase 5 returns immediately with "Review complete" (no refine/complete question)

The caller receives findings with their original classifications intact and decides what to do with them.

Callers invoke headless mode by including mode:headless in the skill arguments, e.g.:

Skill("compound-engineering:document-review", "mode:headless docs/plans/my-plan.md")

If mode:headless is not present, the skill runs in its default interactive mode with no behavior change.

Phase 1: Get and Analyze Document

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

If no document is specified (interactive mode): 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).

If no document is specified (headless mode): Output "Review failed: headless mode requires a document path. Re-invoke with: Skill("compound-engineering:document-review", "mode:headless ")" without dispatching agents.

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 makes challengeable claims about what to build and why, or when the proposed work carries strategic weight beyond the immediate problem. The system's users may be end users, developers, operators, maintainers, or any other audience -- the criteria are domain-agnostic. Check for either leg:

*Leg 1 — Premise claims:* The document stakes a position on what to build or why that a knowledgeable stakeholder could reasonably challenge -- not merely describing a task or restating known requirements:

  • Problem framing where the stated need is non-obvious or debatable, not self-evident from existing context
  • Solution selection where alternatives plausibly exist (implicit or explicit)
  • Prioritization decisions that explicitly rank what gets built vs deferred
  • Goal statements that predict specific user outcomes, not just restate constraints or describe deliverables

*Leg 2 — Strategic weight:* The proposed work could affect system trajectory, user perception, or competitive positioning, even if the premise is sound:

  • Changes that shape how the system is perceived or what it becomes known for
  • Complexity or simplicity bets that affect adoption, onboarding, or cognitive load
  • Work that opens or closes future directions (path dependencies, architectural commitments)
  • Opportunity cost implications -- building this means not building something else

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")
  • Coverage attribution: Attribute the merged finding to the persona with the highest confidence. Decrement the losing persona's Findings count *and* the corresponding route bucket (Auto or Present) so Findings = Auto + Present stays exact.

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

Severity and autofix_class are independent. A P1 finding can be auto if the correct fix is obvious. The test is not "how important?" but "is there one clear correct fix, or does this require judgment?"

Autofix ClassRoute
autoApply automatically -- one clear correct fix. Includes both internal reconciliation (one part authoritative over another) and additions mechanically implied by the document's own content.
presentPresent individually for user judgment

Demote any auto finding that lacks a suggested_fix to present.

Auto-eligible patterns: summary/detail mismatch (body is authoritative over overview), wrong counts, missing list entries derivable from elsewhere in the document, stale internal cross-references, terminology drift, prose/diagram contradictions where prose is more detailed, missing steps mechanically implied by other content, unstated thresholds implied by surrounding context, completeness gaps where the correct addition is obvious. If the fix requires judgment about *what* to do (not just *what to write*), it belongs in 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 have one clear correct fix

List every auto-fix in the output summary so the user can see what changed. Use enough detail to convey the substance of each fix (section, what was changed, reviewer attribution). This is especially important for fixes that add content or touch document meaning -- the user should not have to diff the document to understand what the review did.

Present Remaining Findings

Headless mode: Do not use interactive question tools. Output all non-auto findings as a structured text summary the caller can parse and act on:

Document review complete (headless mode).

Applied N auto-fixes:
- <section>: <what was changed> (<reviewer>)
- <section>: <what was changed> (<reviewer>)

Findings (requires judgment):

[P0] Section: <section> — <title> (<reviewer>, confidence <N>)
  Why: <why_it_matters>
  Suggested fix: <suggested_fix or "none">

[P1] Section: <section> — <title> (<reviewer>, confidence <N>)
  Why: <why_it_matters>
  Suggested fix: <suggested_fix or "none">

Residual concerns:
- <concern> (<source>)

Deferred questions:
- <question> (<source>)

Omit any section with zero items. Then proceed directly to Phase 5 (which returns immediately in headless mode).

Interactive mode:

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. 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

Headless mode: Return "Review complete" immediately. Do not ask questions. The caller receives the text summary from Phase 4 and handles any remaining findings.

Interactive mode:

Ask using the platform's interactive question tool -- do not print the question as plain text output:

  • Claude Code: AskUserQuestion
  • Codex: request_user_input
  • Gemini: ask_user
  • Fallback (no question tool available): present numbered options and stop; wait for the user's next message

Offer these two options. Use the document type from Phase 1 to set the "Review complete" description:

  1. Refine again -- Address the findings above, then re-review
  2. Review complete -- description based on document type:

- requirements document: "Create technical plan with ce:plan" - plan document: "Implement with ce:work"

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 caller skills (ce-brainstorm, ce-plan, or external plugin skills that invoke document-review)

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

平台分布

Codex

31.95%
按下载量换算58

Claude

31.49%
按下载量换算57

Cursor

20.23%
按下载量换算36

Gemini CLI

9.76%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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/everyinc/every-marketplace --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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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