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cccskills
免费在 GitHub 公开

gh-cli

Guides agents to access GitHub repositories, pull requests, issues, and APIs through the authenticated gh command-line tool. Covers private repository access and recommends cloning repositories to read files locally, with commands for viewing GitHub information.

中文简介正在准备中。当前显示英语简介。

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Enforces authenticated gh CLI workflows over unauthenticated curl, WebFetch, and MCP fetch patterns. Use when working with GitHub URLs, API access, pull requests, or issues.

集成工具GitHub
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适用场景

  • Viewing GitHub pull requests and issues
  • Accessing private repositories with authentication
  • Querying the GitHub API through gh
  • Cloning a repository to inspect its files

包含的文件(3)

  • SKILL.md1.2 KB
  • agents/openai.yaml219 B
  • assets/trail-of-bits-mark.svg3.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

gh-cli

When to Use

  • Working with GitHub repositories, pull requests, issues, releases, or raw file URLs.
  • You need authenticated access to private repositories or higher API rate limits.
  • You are about to use curl, wget, WebFetch, or an MCP fetch tool against GitHub.

When NOT to Use

  • The target is not GitHub.
  • Plain local git operations already solve the task.

Guidance

Prefer the authenticated gh CLI over raw HTTP fetches for GitHub content. In particular:

  • Prefer gh repo view, gh pr view, gh pr list, gh issue view, and gh api over unauthenticated curl or wget.
  • Prefer cloning a repository and reading files locally over fetching raw.githubusercontent.com blobs directly.
  • Avoid using GitHub API /contents/ endpoints as a substitute for cloning and reading repository files.

Examples:

gh repo view owner/repo
gh pr view 123 --repo owner/repo
gh api repos/owner/repo/pulls

For the hook implementation, see:

  • plugins/gh-cli/README.md
  • plugins/gh-cli/hooks/

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同一仓库的技能

Build and test code with AddressSanitizer, a tool that detects invalid memory access during execution. Configure checks for C/C++ and unsafe Rust, investigate crash reports, and adjust settings for fuzzing, or testing with generated inputs.

中文简介正在准备中。当前显示英语简介。

  • Detect memory errors while fuzzing C/C++
  • Test unsafe Rust and calls to external libraries
  • Interpret an ASan crash report
trailofbits/skills76412026年10月16日 更新

aflpp

免费

Sets up AFL++ to test C/C++ programs with varied generated inputs, a technique called fuzzing. Covers running tests across CPU cores, monitoring progress, reducing input collections, and reproducing crashes for investigation.

中文简介正在准备中。当前显示英语简介。

  • Running C/C++ fuzzing across multiple CPU cores
  • Exploring further after libFuzzer progress stalls
  • Monitoring fuzzing progress and stability
trailofbits/skills76412026年10月16日 更新

Audits GitHub Actions workflows that run AI coding agents. Traces how attacker-controlled content reaches prompts, checks permissions and sandbox settings, and reports evidence, severity, and fixes for prompt injection and related configuration risks.

中文简介正在准备中。当前显示英语简介。

  • Reviewing workflows that run AI coding agents
  • Tracing issue and PR content into agent prompts
  • Checking sandbox settings and user allowlists
trailofbits/skills76412026年10月16日 更新

Reviews Algorand smart contracts written in TEAL or PyTeal for 11 vulnerability patterns. Produces a complete coverage table and findings with code references, severity ratings, and suggested fixes, with optional automated checks using Tealer.

中文简介正在准备中。当前显示英语简介。

  • Security checks before an Algorand contract audit
  • Reviewing TEAL or PyTeal transaction validation
  • Verifying fixes for reported vulnerabilities
trailofbits/skills76412026年10月16日 更新

atheris

免费

Set up Atheris to test Python code and C extensions with automatically varied inputs. It guides test harness creation, coverage tracking to explore more code, and AddressSanitizer setup for finding memory errors.

中文简介正在准备中。当前显示英语简介。

  • Fuzzing a Python package or parser
  • Investigating memory corruption in Python C extensions
  • Turning raw bytes into typed test arguments
trailofbits/skills76412026年10月16日 更新

Connect static analysis results and human audit notes to a Trailmark code graph. Group findings by severity and compare them with input flow, impact, and privilege boundaries to prioritize investigation and understand findings in their code context.

中文简介正在准备中。当前显示英语简介。

  • Connecting Semgrep or CodeQL results to code structure
  • Combining human audit notes with automated findings
  • Prioritizing findings using input flow and impact
trailofbits/skills76412026年10月16日 更新

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