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Agent Skill · 研究检索

full-review(全面审查)

full-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。

full-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 67,439。

总安装 245周安装 10GitHub Stars 3下载 78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:full-review(全面审查)
来源仓库:https://github.com/iuliandita/skills
仓库路径:skills/full-review
安装命令:
npx skills add https://github.com/iuliandita/skills --skill full-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/iuliandita/skills --skill full-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。

full-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息筛选的场景。通过安装命令从指定仓库添加技能,可结合原始 README 核验用法。

安装前建议确认权限范围和维护状态,避免触发不必要的数据访问。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/full-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/iuliandita/skills --skill full-review;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

full-review 怎么安装?

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

full-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。

full-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/iuliandita/skills --skill full-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。

full-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。

full-review 用的人多吗?

公开数据是累计安装 245 次,近一周安装 10 次,下载 78 次,GitHub 3 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。

full-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。

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
full-review

全面审查 · 本页

2453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

Full Review: Quad Audit Orchestrator

Run four independent audits in parallel and present each report separately. One command that catches bugs, slop, security issues, and stale docs across the entire codebase without invoking each skill manually.

The four audits:

  1. Code Review (code-review skill) - bugs, logic errors, edge cases, race conditions, resource leaks, convention violations. Uses confidence-based filtering (>= 80%), adversarial self-check, and evidence-based verification.
  2. Slop Check (anti-slop skill) - machine-generated patterns, over-abstraction, verbose code, stale idioms
  3. Security Audit (security-audit skill) - vulnerabilities, secrets, dependency risks, OWASP mapping
  4. Docs Sweep (update-docs skill) - stale docs, bloated instruction files, missing gotchas, broken links, companion-file drift

Each audit runs in its own parallel agent/subprocess with a fresh context window, so they don't compete for tokens or bias each other's findings.

When to use

  • Running a repo-wide quality gate before merge, release, or handoff
  • Auditing an unfamiliar codebase across correctness, security, slop, and docs in one pass
  • Getting a broad review when the user explicitly wants multiple audit lenses at once

When NOT to use

  • A targeted correctness review on specific files - use code-review
  • Style/slop cleanup without the other audit passes - use anti-slop
  • A dedicated security review only - use security-audit
  • A documentation-only maintenance sweep - use update-docs
  • A comprehensive audit across all applicable skills (up to 21) - use deep-audit
  • Auditing the skill collection for consistency or quality - use skill-creator

AI Self-Check

Run this checklist after all agents return but before presenting the combined report to the user. Do not present results until every item passes.

Verify:

  • All 4 agents dispatched as general-purpose type (NOT feature-dev:*, code-simplifier:*, or other restricted types)
  • Each agent invoked its assigned custom skill (code-review, anti-slop, security-audit, update-docs) via the Skill tool
  • Each report presented under its own header, unedited
  • No cross-report merging or editorializing (findings from different audits stay separate)
  • SECURITY-AUDIT.md gitignore reminder included
  • Failed agents noted with reason (don't silently drop a missing audit)
  • Preflight context block was passed to all agents
  • When user specified a scope, the Scope: line in every agent's context block reflects that scope (not "full codebase review")
  • Scope held in output: each agent's findings reference only files/modules within the requested scope. If any agent's output references out-of-scope paths, flag it in that report's header (see Step 3 scope verification)

Workflow

Step 0: Preflight

Gather context before dispatching agents. Run these in parallel (guard each with ; true so one failure doesn't cancel siblings):

  1. Repo state: git rev-parse --show-toplevel; true and git rev-parse --short HEAD; true
  2. Branch: git branch --show-current; true
  3. Language detection: check for manifest files (package.json, requirements.txt, go.mod, Cargo.toml, pyproject.toml, composer.json, Gemfile, *.tf, helmfile.yaml)
  4. Repo size estimate: git ls-files | wc -l; true

If not a git repo (step 1 fails): stop and tell the user. The audits rely on git context (history, blame, diff). Running without it produces low-quality results.

Record preflight values - each subagent prompt uses them. Substitute {placeholders} in the agent prompts below with the actual values from preflight (e.g., replace {repo_root} with the output of git rev-parse --show-toplevel). Default {scope} to "full codebase review - scan everything"; override in Step 1 if the user specifies a narrower target.

Step 1: Determine Scope

Default is full codebase since the user is running this as a quality gate. Adapt if context suggests otherwise:

  • Uncommitted changes present -> mention this, but still audit the full repo.
  • Detached HEAD / bare repo -> warn the user, proceed with what's available.
  • User specified a narrower scope (specific files, directory, module) -> pass that scope constraint to all four agents. Each agent only audits within the specified scope. This is the key to scoped reviews: narrowing the target, not the audit dimensions. Set {scope} in the context block to the user's scope (e.g., "src/auth/ directory only") instead of the default "full codebase review - scan everything".

Step 2: Dispatch Four Parallel Agents

Spawn all four agents concurrently. Each agent invokes one of the four custom skills and runs a full codebase audit.

Agent type selection (critical): Each agent MUST be dispatched as a general-purpose agent (or equivalent full-access agent type). Do NOT use specialized agent types like feature-dev:code-reviewer, feature-dev:code-explorer, code-simplifier:*, or any other restricted-toolset agent - these lack access to the Skill tool and cannot invoke custom skills. The agent type name should reflect its capabilities (full tool access), not the audit it performs.

Skill invocation: Each general-purpose agent MUST invoke the named custom skill via the Skill tool (or equivalent skill-loading mechanism) as its first action. Custom skills from the user's installed collection take priority over built-in reviewers or platform-provided audit modes. Specifically:

  • Agent 1 invokes code-review via Skill tool, not a built-in code-review mode
  • Agent 2 invokes anti-slop via Skill tool, not a built-in code simplifier
  • Agent 3 invokes security-audit via Skill tool, not a built-in security scanner
  • Agent 4 invokes update-docs via Skill tool, not a built-in documentation reviewer

Fallback: If a custom skill is not available (skill lookup/load returns "not found" or similar), THEN fall back to the best available alternative (manual review following the skill's principles) and note which skill was unavailable in the output header.

If parallel execution is unavailable (restricted sandbox, no subagent support): run sequentially in this order: Security Audit, Code Review, Slop Check, Docs Sweep. Security first because those findings are most time-sensitive. If any agent exceeds 5 minutes wall-clock, note the timeout in the output header and continue with the remaining agents.

If agent dispatch is unavailable (non-Claude harness, no subagent API): run each audit sequentially in separate CLI sessions, invoking each skill manually in its own conversation.

Pass this context block to every agent, substituting the {placeholders} from preflight:

Context:
- Repo: {repo_root}
- Commit: {short_sha}
- Branch: {branch}
- Languages: {detected_languages}
- File count: {file_count}
- Scope: {scope}

Each agent receives the context block above plus a task prompt. Use these templates:

Agent 1: Code Review
{context_block}

Invoke the `code-review` skill via the Skill tool, then run a full code review on the codebase.
Scope: {scope}. Return the complete report.
Agent 2: Slop Check
{context_block}

Invoke the `anti-slop` skill via the Skill tool, then audit the codebase for machine-generated
patterns, over-abstraction, and code quality issues. Scope: {scope}. Return the complete report.
Agent 3: Security Audit
{context_block}

Invoke the `security-audit` skill via the Skill tool, then run a security audit on the codebase.
Scope: {scope}. Return the complete report including SECURITY-AUDIT.md content.
Agent 4: Docs Sweep
{context_block}

Invoke the `update-docs` skill via the Skill tool as a read-only audit. Scope: {scope}.
Focus on: stale docs, instruction-file bloat (40,000 char limit), companion-file drift, broken
links, orphaned gotchas, missing docs on recent changes. Do NOT make changes or commit anything.
Return the complete report.

Step 3: Present Results

After all four agents return, present each report under its own header. Do not merge, summarize, or editorialize across reports - each stands alone. The user reads the skill's native output, not a reinterpretation.

Scoped reviews: when the user specified a narrower scope, each report focuses on that scope. Use this routing table to emphasize domain-relevant checks:

Scopecode-review focussecurity-audit focusanti-slop focusupdate-docs focus
Auth/sessionAuth logic paths, token lifecycleSession handling, token validation, credential storageAuth middleware over-abstractionAuth-related docs current
API endpointsRequest/response handling, error pathsInput validation, injection, rate limitingHandler boilerplate, verbose error wrappingAPI docs, OpenAPI spec
Data layerQuery correctness, race conditionsSQL injection, data exposure, access controlORM abstraction, unnecessary wrappersSchema docs, migration notes
InfrastructureConfig correctness, resource handlingSecrets exposure, misconfigurationOver-engineered deploy scriptsInfra docs, runbook accuracy

For scopes not in the table, apply each skill's standard checklist narrowed to the specified files/module. Do not skip an audit just because the scope seems domain-specific - every skill may surface relevant findings on arbitrary code.

Scope verification before presenting: when a scope was specified, confirm each agent's output before including it in the report. If an agent's findings reference files or modules outside the requested scope, that agent ignored the scope constraint - note the discrepancy in its report header and, if possible, filter out-of-scope findings. If an agent returned zero findings, confirm it actually ran against the scoped target (not an empty or wrong path) before reporting "no issues found."

User requests synthesis: if the user asks for a combined summary after seeing the reports, prioritize: security fixes > correctness bugs > slop cleanup > doc updates. Keep synthesis brief - the individual reports are the source of truth.

After presenting results, remind the user: "Check that SECURITY-AUDIT.md is in .gitignore - it contains vulnerability details that shouldn't be committed."

Use this structure:

# Full Review: {repo_name} @ {short_sha}

Languages: {detected_languages} | Files: {file_count} | Branch: {branch}
Scope: {scope}

---

## 1. Code Review

{agent 1 output verbatim}

---

## 2. Slop Check

{agent 2 output verbatim}

---

## 3. Security Audit

{agent 3 output verbatim}

---

## 4. Docs Sweep

{agent 4 output verbatim}

---

Step 4: Handle Failures

If an agent fails or times out:

  • Note which audit failed and why (timeout, skill not found, tool permission denied)
  • Present whatever completed successfully
  • Do not re-run failed agents unless the user asks

If a skill is not available, perform a manual review in the same general-purpose agent. Note the substitution in the output header so the user knows a fallback was used. Partial results are still useful.

Unavailable skillFallback approach
code-reviewManually review for bugs, logic errors, edge cases, and resource leaks. Focus on high-confidence findings only.
anti-slopScan for verbose code, redundant comments, over-abstraction, and dead code manually. No structured slop taxonomy - report what you find.
security-auditManually check for hardcoded secrets, injection points, missing auth checks, and dependency CVEs. Skip SECURITY-AUDIT.md generation.
update-docsReview README, CLAUDE.md, AGENTS.md, and inline doc comments for staleness. Check that recent code changes have corresponding doc updates.

Related Skills

  • code-review - one of the four parallel audits. Finds bugs, logic errors, correctness issues.
  • anti-slop - one of the four parallel audits. Finds quality/style issues and AI-generated patterns.
  • security-audit - one of the four parallel audits. Finds vulnerabilities, secrets, dependency risks.
  • update-docs - one of the four parallel audits. Finds stale docs, bloated instruction files, and missing gotchas.
  • skill-creator - audits the skill collection itself. Full-review audits application code.

Rules

  • General-purpose agents only. Every subagent MUST be a general-purpose (full-access) agent type. Never use feature-dev:*, code-simplifier:*, or other restricted agent types - they cannot invoke custom skills. The agent type controls tool access, not the audit topic.
  • Custom skills first. Each agent invokes its assigned custom skill (code-review, anti-slop, security-audit, update-docs) via the Skill tool as its first action. Fall back to manual review only if the skill is not installed.
  • Parallel dispatch is strongly preferred. Run all four agents concurrently when the environment supports it. If parallel execution is unavailable, run sequentially (security first - see Step 2).
  • Don't editorialize. Present each report as the skill produced it. No unsolicited synthesis across reports.
  • Respect each skill's output format. The anti-slop skill has its own format. The security audit writes SECURITY-AUDIT.md. The code reviewer and docs sweep have their formats. Don't normalize them into a single style.
  • Don't duplicate work. If a finding appears in multiple reports (e.g., dead code in both slop check and code review), that's fine - independent auditors catching the same thing is signal, not noise.
  • Preflight is fast. The parallel git commands in Step 0 should take under 2 seconds. Don't skip them - the agent prompts are much better with context.
  • Large repos. If file count exceeds 1000, mention to the user that this will take a while. Don't reduce scope unless asked.
  • SECURITY-AUDIT.md gitignore. The security audit writes a report file containing vulnerability details to the repo root. After presenting results, remind the user to check that SECURITY-AUDIT.md is in .gitignore - the sub-skill warns too, but it's easy to miss buried in output.
  • Docs sweep is read-only. The update-docs agent must not make changes or commit anything during a full review. It reports what needs updating; the user decides when to act on it.

平台分布

Codex

34.55%
按下载量换算27

Claude

27.87%
按下载量换算22

Cursor

21.45%
按下载量换算17

Gemini CLI

10.7%
按下载量换算8

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/iuliandita/skills --skill full-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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