Create a skillsaw rule plugin — a pip-installable Python package that adds custom lint rules to skillsaw. Walks through scaffolding the package, writing rules against the lint tree, testing, and publishing to PyPI. Use when a user wants to share skillsaw rules across repositories or publish them for others.
Survey the AI coding assistant and agentic tool ecosystem, assess skillsaw's competitive position, identify emerging patterns and missing capabilities, and produce a prioritized strategic report as a GitHub issue. Use when evaluating ecosystem trends and product gaps.
Fix skillsaw lint violations — apply deterministic autofixes, then resolve the remaining violations with targeted edits guided by skillsaw explain. Use when skillsaw reports violations, when asked to clean up lint findings, or after skillsaw fix leaves violations behind.
Triage a GitHub issue filed against skillsaw — classify it (bug, feature, docs, question, other), verify its claims against the codebase, enrich it with missing details, and post one structured triage comment. Use when triaging and labeling incoming issues, not to fix them.
Use when skillsaw reports a likely false positive, misses an edge case, behaves incorrectly, or needs an RFE. Gather a safe report and, only with explicit user permission, create a feedback bundle or open a GitHub issue.
Use when modifying agentic contextual building blocks like skills (SKILL.md), slash commands, agents, hooks, plugins, marketplaces, and instruction files (CLAUDE.md, AGENTS.md, GEMINI.md, QWEN.md, Cursor, Copilot, Cline, or Kiro rules), and tool configuration such as an OpenCode opencode.json. Run skillsaw on the…
Analyze upstream specs (agentskills.io, Claude Code plugin/marketplace format, OpenAI Codex plugins/marketplace, OpenClaw, MCP and MCP Registry, CodeRabbit, APM) for changes, identify gaps in skillsaw's rule coverage, and create or update PRs to close those gaps. Use when performing periodic maintenance on the…
Onboard a repository to skillsaw — run the linter, apply autofixes, manually fix remaining violations, set up CI, and create a baseline. Use when adopting skillsaw on a new or existing project.
Follow up on open PRs in skillsaw — fix failing CI, address reviewer feedback, push updates, and validate backward compatibility. Use when an open PR needs maintenance.
Use when reviewing a skillsaw PR. Dispatches 7 specialist reviewers (Architecture, Python Expert, Security & Supply Chain, QA Engineer, Technical Writer, Ecosystem, Slopinator) as parallel sub-agents by default, then synthesizes a single verdict. Use --serial for cheaper inline execution.