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Browser-based UI test execution against live clusters
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Analyze upstream specs (agentskills.io, Claude Code plugin/marketplace format, OpenClaw, MCP, 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 skillsaw linter.
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.
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.
| name | ui-test |
| description | Browser-based UI test execution against live clusters |
| user-invocable | true |
| allowedTools | ["Bash(python3 *scripts/run_tests.py*)","Bash(python3 *scripts/collect_results.py*)","Read","Write"] |
Runs browser-based UI tests against live clusters.
