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Agent Skill · 研究检索

audit-context-building(审计环境构建)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

audit-context-building 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 40,169。

总安装 1,320周安装 55GitHub Stars 35,717下载 440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:audit-context-building(审计环境构建)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/audit-context-building
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill audit-context-building
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/sickn33/antigravity-awesome-skills --skill audit-context-building

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。

用于安全审计环境的搭建与凭证检查。audit-context-building 属于研究检索类 Skill,可作为该场景下的辅助能力补充。支持权限配置、依赖漏洞和认证流程的分析。适合内网或生产系统的安全复核任务。通过 GitHub 安装,涉及密钥时应启用最小权限原则。所有操作必须经过授权并保留审计日志。

来源仓库内路径:skills/audit-context-building

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/sickn33/antigravity-awesome-skills --skill aud…;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

audit-context-building 怎么安装?

在终端执行 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill audit-context…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

audit-context-building 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。

audit-context-building 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/sickn33/antigravity-awesome-skills --skill audit-context-building 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。

audit-context-building 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。

audit-context-building 用的人多吗?

公开数据是累计安装 1,320 次,近一周安装 55 次,下载 440 次,GitHub 35,717 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。

audit-context-building 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 35,717 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
audit-context-building

审计环境构建 · 本页

1,32035,717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

Deep Context Builder Skill (Ultra-Granular Pure Context Mode)

1. Purpose

This skill governs how Claude thinks during the context-building phase of an audit.

When active, Claude will:

  • Perform line-by-line / block-by-block code analysis by default.
  • Apply First Principles, 5 Whys, and 5 Hows at micro scale.
  • Continuously link insights → functions → modules → entire system.
  • Maintain a stable, explicit mental model that evolves with new evidence.
  • Identify invariants, assumptions, flows, and reasoning hazards.

This skill defines a structured analysis format (see Example: Function Micro-Analysis below) and runs before the vulnerability-hunting phase.


When to Use

Use when:

  • Deep comprehension is needed before bug or vulnerability discovery.
  • You want bottom-up understanding instead of high-level guessing.
  • Reducing hallucinations, contradictions, and context loss is critical.
  • Preparing for security auditing, architecture review, or threat modeling.

Do not use for:

  • Vulnerability findings
  • Fix recommendations
  • Exploit reasoning
  • Severity/impact rating

3. How This Skill Behaves

When active, Claude will:

  • Default to ultra-granular analysis of each block and line.
  • Apply micro-level First Principles, 5 Whys, and 5 Hows.
  • Build and refine a persistent global mental model.
  • Update earlier assumptions when contradicted ("Earlier I thought X; now Y.").
  • Periodically anchor summaries to maintain stable context.
  • Avoid speculation; express uncertainty explicitly when needed.

Goal: deep, accurate understanding, not conclusions.


Rationalizations (Do Not Skip)

RationalizationWhy It's WrongRequired Action
"I get the gist"Gist-level understanding misses edge casesLine-by-line analysis required
"This function is simple"Simple functions compose into complex bugsApply 5 Whys anyway
"I'll remember this invariant"You won't. Context degrades.Write it down explicitly
"External call is probably fine"External = adversarial until proven otherwiseJump into code or model as hostile
"I can skip this helper"Helpers contain assumptions that propagateTrace the full call chain
"This is taking too long"Rushed context = hallucinated vulnerabilities laterSlow is fast

4. Phase 1 — Initial Orientation (Bottom-Up Scan)

Before deep analysis, Claude performs a minimal mapping:

  1. Identify major modules/files/contracts.
  2. Note obvious public/external entrypoints.
  3. Identify likely actors (users, owners, relayers, oracles, other contracts).
  4. Identify important storage variables, dicts, state structs, or cells.
  5. Build a preliminary structure without assuming behavior.

This establishes anchors for detailed analysis.


5. Phase 2 — Ultra-Granular Function Analysis (Default Mode)

Every non-trivial function receives full micro analysis.

5.1 Per-Function Microstructure Checklist

For each function:

  1. Purpose

- Why the function exists and its role in the system.

  1. Inputs & Assumptions

- Parameters and implicit inputs (state, sender, env). - Preconditions and constraints.

  1. Outputs & Effects

- Return values. - State/storage writes. - Events/messages. - External interactions.

  1. Block-by-Block / Line-by-Line Analysis For each logical block: Apply per-block:

- What it does. - Why it appears here (ordering logic). - What assumptions it relies on. - What invariants it establishes or maintains. - What later logic depends on it. - First Principles - 5 Whys - 5 Hows


5.2 Cross-Function & External Flow Analysis

*(Full Integration of Jump-Into-External-Code Rule)*

When encountering calls, continue the same micro-first analysis across boundaries.

Internal Calls
  • Jump into the callee immediately.
  • Perform block-by-block analysis of relevant code.
  • Track flow of data, assumptions, and invariants: caller → callee → return → caller.
  • Note if callee logic behaves differently in this specific call context.
External Calls — Two Cases

Case A — External Call to a Contract Whose Code Exists in the Codebase Treat as an internal call:

  • Jump into the target contract/function.
  • Continue block-by-block micro-analysis.
  • Propagate invariants and assumptions seamlessly.
  • Consider edge cases based on the *actual* code, not a black-box guess.

Case B — External Call Without Available Code (True External / Black Box) Analyze as adversarial:

  • Describe payload/value/gas or parameters sent.
  • Identify assumptions about the target.
  • Consider all outcomes:

- revert - incorrect/strange return values - unexpected state changes - misbehavior - reentrancy (if applicable)

Continuity Rule

Treat the entire call chain as one continuous execution flow. Never reset context. All invariants, assumptions, and data dependencies must propagate across calls.


5.3 Complete Analysis Example

See FUNCTION_MICRO_ANALYSIS_EXAMPLE.md for a complete walkthrough demonstrating:

  • Full micro-analysis of a DEX swap function
  • Application of First Principles, 5 Whys, and 5 Hows
  • Block-by-block analysis with invariants and assumptions
  • Cross-function dependency mapping
  • Risk analysis for external interactions

This example demonstrates the level of depth and structure required for all analyzed functions.


5.4 Output Requirements

When performing ultra-granular analysis, Claude MUST structure output following the format defined in OUTPUT_REQUIREMENTS.md.

Key requirements:

  • Purpose (2-3 sentences minimum)
  • Inputs & Assumptions (all parameters, preconditions, trust assumptions)
  • Outputs & Effects (returns, state writes, external calls, events, postconditions)
  • Block-by-Block Analysis (What, Why here, Assumptions, First Principles/5 Whys/5 Hows)
  • Cross-Function Dependencies (internal calls, external calls with risk analysis, shared state)

Quality thresholds:

  • Minimum 3 invariants per function
  • Minimum 5 assumptions documented
  • Minimum 3 risk considerations for external interactions
  • At least 1 First Principles application
  • At least 3 combined 5 Whys/5 Hows applications

5.5 Completeness Checklist

Before concluding micro-analysis of a function, verify against the COMPLETENESS_CHECKLIST.md:

  • Structural Completeness: All required sections present (Purpose, Inputs, Outputs, Block-by-Block, Dependencies)
  • Content Depth: Minimum thresholds met (invariants, assumptions, risk analysis, First Principles)
  • Continuity & Integration: Cross-references, propagated assumptions, invariant couplings
  • Anti-Hallucination: Line number citations, no vague statements, evidence-based claims

Analysis is complete when all checklist items are satisfied and no unresolved "unclear" items remain.


6. Phase 3 — Global System Understanding

After sufficient micro-analysis:

  1. State & Invariant Reconstruction

- Map reads/writes of each state variable. - Derive multi-function and multi-module invariants.

  1. Workflow Reconstruction

- Identify end-to-end flows (deposit, withdraw, lifecycle, upgrades). - Track how state transforms across these flows. - Record assumptions that persist across steps.

  1. Trust Boundary Mapping

- Actor → entrypoint → behavior. - Identify untrusted input paths. - Privilege changes and implicit role expectations.

  1. Complexity & Fragility Clustering

- Functions with many assumptions. - High branching logic. - Multi-step dependencies. - Coupled state changes across modules.

These clusters help guide the vulnerability-hunting phase.


7. Stability & Consistency Rules

*(Anti-Hallucination, Anti-Contradiction)*

Claude must:

  • Never reshape evidence to fit earlier assumptions. When contradicted:

- Update the model. - State the correction explicitly.

  • Periodically anchor key facts Summarize core:

- invariants - state relationships - actor roles - workflows

  • Avoid vague guesses Use:

- "Unclear; need to inspect X." instead of: - "It probably…"

  • Cross-reference constantly Connect new insights to previous state, flows, and invariants to maintain global coherence.

8. Subagent Usage

Claude may spawn subagents for:

  • Dense or complex functions.
  • Long data-flow or control-flow chains.
  • Cryptographic / mathematical logic.
  • Complex state machines.
  • Multi-module workflow reconstruction.

Use the function-analyzer agent for per-function deep analysis. It follows the full microstructure checklist, cross-function flow rules, and quality thresholds defined in this skill, and enforces the pure-context-building constraint.

Subagents must:

  • Follow the same micro-first rules.
  • Return summaries that Claude integrates into its global model.

9. Relationship to Other Phases

This skill runs before:

  • Vulnerability discovery
  • Classification / triage
  • Report writing
  • Impact modeling
  • Exploit reasoning

It exists solely to build:

  • Deep understanding
  • Stable context
  • System-level clarity

10. Non-Goals

While active, Claude should NOT:

  • Identify vulnerabilities
  • Propose fixes
  • Generate proofs-of-concept
  • Model exploits
  • Assign severity or impact

This is pure context building only.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

平台分布

Codex

33.8%
按下载量换算149

Claude

30.87%
按下载量换算136

Cursor

20.49%
按下载量换算90

Gemini CLI

9.32%
按下载量换算41

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/sickn33/antigravity-awesome-skills --skill audit-context-building 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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