Total 43,570 skills, Project Management has 1608 skills
Showing 12 of 1608 skills
When developing new features, follow this sub-process — take the vague idea of "add X capability" through to the acceptance closure, with solution documents archived so that both AI and users can later check the original thinking and decision rationale. Trigger scenarios are focused on adding new capabilities ("develop new feature", "add X", "implement XX"), and do not handle bugs in existing code. This skill only acts as a router, deciding which sub-skill to trigger next among brainstorm / design / fastforward / implement / acceptance based on existing artifacts.
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, 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.
Full task lifecycle: create → assign → monitor → review → reject/complete. Use when asked to "add a feature", "fix a bug", "create a task", "加个功能", "修个 bug", or "/ak-task <description>".
Systematic Fishbone analysis exploring problem causes across six categories
Use when a docs-driven repository has a selected or selectable concrete docs/tasks task and needs task-local spec or implementation governance before code changes.
Use when a request or repository needs roadmap decomposition before spec writing because milestone boundaries, module grouping, or independently reviewable tasks are unclear.
Generate a phase-based task breakdown in tasks.md from spec.md and plan.md
Write a plan file for a multi-step task (Step 3 of /task). Runs one brainstorming round then writes ai-workspace/plans/<name>.md from TEMPLATE.md. Skipped for one-sentence scope. Does NOT review — that is /review (Step 4).
Documents backlog refinement session outcomes including stories refined, estimates, questions raised, and decisions made. Use during or after refinement to capture the results and share with absent team members.
Kanban / task board with columns (To do / In progress / In review / Done), draggable-looking cards, assignee avatars, swimlanes, and a top filter bar. Use when the brief mentions "kanban", "task board", "sprint board", "trello", "看板".
Use when starting any development task beyond single-line fixes — classifies the request, detects current project phase, and routes to the right specification or execution tool