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.
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.
Review the instructions the agent will receive before you install.
curl, wget, WebFetch, or an MCP fetch tool against GitHub.Prefer the authenticated gh CLI over raw HTTP fetches for GitHub content. In particular:
gh repo view, gh pr view, gh pr list, gh issue view, and gh api over unauthenticated curl or wget.raw.githubusercontent.com blobs directly./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:
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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.
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.
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.
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.
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.
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.