dev-planning
The dev-planning skill guides creation and updates of AI feature implementation plans within the AI DevKit framework. Use it when establishing initial task lists from requirements and design docs, tracking progress across implementation work, documenting blockers, capturing newly discovered tasks, or reconciling plan status during development phases. It enforces linting validation, task traceability to requirements and testing scenarios, milestone organization, and dependency mapping.
git clone --depth 1 https://github.com/codeaholicguy/ai-devkit /tmp/dev-planning && cp -r /tmp/dev-planning/skills/dev-planning ~/.claude/skills/dev-planningSKILL.md
# Dev Planning Run planning creation and reconciliation for configured AI docs features. Before changing docs, propose the concrete plan for this phase and wait for user approval unless the user already approved the exact phase plan. ## Phase Contract 1. Run `npx ai-devkit@latest lint` before phase work. 2. If working on a named feature, run `npx ai-devkit@latest lint --feature <name>`. 3. Read existing configured planning, implementation, and testing docs before changes. Resolve paths through `lint --feature` instead of assuming `docs/ai`. 4. Keep task creation and updates traceable to requirements, design, testing scenarios, completed work, blockers, or newly discovered scope. 5. If parent `dev-lifecycle` established usable task tracing, emit planning phase, progress, blocker/scope, and next-step events per `task`. ## Create Initial Plan Use for Phase 4 after requirements, design, and initial testing docs exist. 1. Run `npx ai-devkit@latest lint --feature <name>` and identify the planning doc path it validates. If `docs init-feature` just ran, use the returned planning path as authoritative. 2. Read requirements, design, and testing docs for the feature. 3. Convert goals, user stories, design components, API/data changes, migration needs, and testing scenarios into implementation tasks. 4. Group tasks by milestone or logical sequence. 5. For each task, include outcome, dependencies, validation evidence, and related testing scenarios. 6. Verify every test-plan scenario has at least one implementation task. 7. Add risks, blockers, sequencing notes, and likely follow-up checks. 8. Update the planning doc with the initial ordered task list. 9. If task tracing is available, record plan progress and next implementation step per `task`. Next: `dev-implementation`. ## Update Planning Use for Phase 6. Auto-trigger this phase after completing any task in `dev-implementation`. 1. Run `npx ai-devkit@latest lint --feature <name>` and reconcile the planning doc path it validates. If manual path resolution is unavoidable, first resolve `.ai-devkit.json` `paths.docs`, falling back to `docs/ai`. 2. If continuing from implementation, carry forward existing context. Otherwise ask for feature name, completed tasks, new tasks, blockers, and planning doc path. 3. Review existing milestones, sequencing, dependencies, and outstanding tasks. 4. Reconcile each task: mark status as done, in-progress, blocked, or not started; note scope changes; record blockers; capture skipped or added tasks. 5. Update the planning doc with the current status checklist. 6. Suggest the next 2-3 actionable tasks, risky areas, and coordination needed. 7. If task tracing is available, record completed/blocked/new tasks, blockers, and next action per `task`. 8. Write a summary paragraph for the planning doc covering progress, risks, upcoming focus, and scope changes. Next: if tasks remain, return to `dev-implementation`. If all done, run implementation verification before testing and review.
AI DevKit · Exchange information with active Codex, Claude Code, and other AI agents using ai-devkit agent list, detail, and send. Use when an agent needs to find another active agent, read its recent context, send it information, or request information back.
AI DevKit · Manage running AI agents with ai-devkit agent commands. Use when an agent needs to identify itself, list agents, start workers, inspect agent detail, assign work, group agents, resume sessions, stop agents, or delegate work to other agents.
AI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.
AI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.
AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.
AI DevKit · Design phase guidance for reviewing feature design against requirements. Use when the user wants to validate architecture, review design docs, resolve design trade-offs, or run dev-lifecycle phase 3.