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Guides the agent on how to read and search GitHub issues to understand the repository's problems.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | github-researcher |
| description | Guides the agent on how to read and search GitHub issues to understand the repository's problems. |
This skill helps the agent find and understand issues in a specified GitHub repository, and gain a deep understanding of the codebase.
[!WARNING] GitHub CLI (
gh) is NOT installed in this environment. Do NOT attempt to runghcommands. Always use the providedfetch_issues.pyscript to batch fetch open issues, and usecurlwith the GitHub REST API to fetch specific issue details or comments.
You can fetch issues using the provided Python script (works without auth for public repos):
python skills/github-researcher/scripts/fetch_issues.py --repo <owner>/<repo> --workspace ./workspace
Output: {workspace}/data/github-issues.md
If you need to fetch specific issue details or comments, you can query the GitHub REST API directly using curl (since api.github.com is in the network allowlist):
curl -s -H "User-Agent: Repo-Maintainer/1.0" https://api.github.com/repos/<owner>/<repo>/issues/<issue_number>
curl -s -H "User-Agent: Repo-Maintainer/1.0" https://api.github.com/repos/<owner>/<repo>/issues/<issue_number>/comments
To answer questions like "What are my biggest issues?" or understand the project deeply:
README.md in the cloned repo.find . -maxdepth 2 to understand the structure.Produce a summary of the top issues and codebase structure to answer the user's high-level questions.
Guides the agent on how to handle git operations and generate .patch files instead of submitting PRs.
Records and appends every user-agent customer support interaction to the memory.md log in the workspace.
Scans a website deeply, converting HTML pages to markdown, respecting robots.txt, and updating the snapshots log.
Exposes a 100% local, offline PDF batch extraction utility (extract_to_markdown.py) that isolates invoices under invoices/ and translates PDFs into clean Markdown files for LLM-native parsing.
Reconcile loaded expenses against the pre-parsed invoice database, flagging discrepancies like amount mismatches, missing invoices, and merchant mismatches locally.
Verify whether vendors/merchants from expense records are real, registered business entities by querying the free Wikidata open API.