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Found 21 Skills
This skill provides a systematic approach for investigating and fixing bugs and issues in the codebase. Use this skill when users report bugs, unexpected behavior, test failures, or request fixes for specific issues. The skill guides through issue registration, root cause analysis, impact assessment, minimal code changes, quality validation, and E2E testing.
End-to-end GitHub issue fix workflow using gh, local code changes, builds/tests, and git push. Use when asked to take an issue number, inspect the issue via gh, implement a fix, run XcodeBuildMCP builds/tests, commit with a closing message, and push.
Fixes GitHub issues from a provided issue URL. Creates a feature branch, implements the fix, updates docs and agent skill when needed, and opens a pull request. Use when given a GitHub issue link or asked to fix/resolve an issue and create a PR.
Issue Workflow Stage 3——Fix code precisely based on confirmed root cause and solution, verify the effect, and document it in {slug}-fix-note.md. This is the final stage of the issue workflow—no verification loop means the workflow is incomplete. Two entry points: the standard path is triggered from easysdd-issue-analyze (with existing {slug}-analysis.md), and the quick path is triggered directly from easysdd-issue-report (without {slug}-analysis.md, as the root cause was determined by AI reading code during the report stage). Trigger scenarios: user says 'Start fixing the bug', 'Fix according to analysis', 'Start modifying code'. During repair, only modify the files stated in the solution; do not optimize casually or introduce new abstractions—these actions will make the scope spread to untraceable levels.
Phase 3 of the issue workflow —— Fix code precisely according to confirmed root causes and solutions, verify the results, and document it in {slug}-fix-note.md. This is the final stage of the issue workflow —— no verification closure means the workflow is incomplete. Two entry points: the standard path is triggered from cs-issue-analyze (with existing {slug}-analysis.md), and the fast track is triggered directly from cs-issue-report (without {slug}-analysis.md, as the root cause was identified by AI through code reading during the report phase). Trigger scenarios: User says "Start fixing the bug", "Fix according to the analysis", "Start modifying the code". During the fix, only modify the files specified in the solution; do not make incidental optimizations or introduce new abstractions —— these actions will cause the scope to expand to an untraceable extent.
Document the pitfalls encountered or good practices discovered during this work into searchable learning documents, so that both AI and humans can look them up when similar tasks arise in the future. Two tracks: The pitfall track records experiences where "things should have worked but didn't" — bugs, configuration traps, environment issues, integration failures; The knowledge track records findings that "should be the default approach going forward" — best practices, workflow improvements, reusable patterns. Trigger scenarios: Proactively prompt for input when wrapping up feature-acceptance or issue-fix, or when the user says phrases like "document knowledge", "learning", "document learnings", "record this experience". Spec documents record what was done and how it was done, while learning documents record what pitfalls were encountered / what was learned — the two complement each other and are not interchangeable.
Document the pitfalls encountered or good practices discovered during this work into searchable learning documents, which can be accessed by both AI and humans when similar tasks arise in the future. Two tracks: The pitfall track records experiences where "things should have worked but didn't" — including bugs, configuration traps, environment issues, and integration failures; The knowledge track records findings that "should be the default approach going forward" — including best practices, workflow improvements, and reusable patterns. Trigger scenarios: Proactively prompt at the end of feature-acceptance or issue-fix workflows, or when the user mentions phrases like "document knowledge", "learning", "document learnings", or "record this experience". Spec documents record what was done, while learning documents record what pitfalls were encountered / what was learned — they complement each other and are not interchangeable.
Review and resolve PR issues with Qodo - get AI-powered code review issues and fix them interactively (GitHub, GitLab, Bitbucket, Azure DevOps)
Review a project's PRs to check for issues detected in code review by Seer Bug Prediction. Use when asked to review or fix issues identified by Sentry in PR comments, or to find recent PRs with Sentry feedback.
Fix GitHub issues end-to-end — from analysis through branch creation, implementation, testing, and PR submission. Use this skill whenever the user mentions fixing a GitHub issue, resolving a bug from an issue tracker, working on a GitHub issue number, or says things like "fix issue
Implement the fix for a GitHub issue from its RCA artifact (created by piv-investigate-issue) — drift-check the plan, branch, implement, add regression tests, and validate. Use after the investigation artifact exists and you're ready to fix the issue.
Run /check-stripe, then fix the highest priority Stripe issue. Creates one fix per invocation. Invoke again for next issue. Use /log-stripe-issues to create issues without fixing.