Splits an epic into PR-sized tasks and registers them as a GitHub Map Issue plus per-task Issues. In design mode it interviews the user, writes a behavior-only design doc with an ADR for each decision that doc states as a fact, and ships those docs as their own PR. In split mode it reads a design doc that already exists and goes straight to the breakdown.
Plugin task-splitter from marketplace k1nak0 in k1nak0/marketplace. Commands read from the repo's manifest — 12 days ago.
design-behaviorTurn a requirements report into a behavior-only design doc under docs/design/, updating docs/design/index.md and merging into docs/prd.md. Reads existing design docs to flag (not auto-resolve) conflicts. Use for Phase 2 of task-splitter, after understand-requirements has written requirements-report.
plan-tasksDecompose a design doc into PR-sized tasks with a dependency graph, acceptance criteria, verification method, and a brief implementation sketch per task. Writes task-breakdown-plan.md. Use for Phase 3 of task-splitter, after design-behavior has written the design doc.
register-tasksRegister a confirmed task breakdown as a GitHub Map Issue plus per-task Issues, using the gh CLI. Use for Phase 5 of task-splitter, after the user has confirmed the task-breakdown-plan.md produced by plan-tasks and Phase 4 has opened the design-doc PR.
task-splitterMain entry point for task-splitter. Runs in one of two modes — design, which interviews the user, writes a behavior-only design doc, splits the epic, ships the docs as a PR and registers GitHub Issues; or split, which reads a design doc that already exists and registers Issues from it. Invoke this s
understand-requirementsEstablish what a task-splitter run is building. In design mode, conduct a full structured requirements interview covering goals, features, constraints, scope boundaries, and definition of done. In split mode, read most of that out of an existing design doc and ask only what the doc cannot answer. Wr
A multi-agent implementation pipeline that takes a GitHub Map Issue task (or a standalone requirement) through user scrutiny, optional Issue refinement, codebase investigation, planning, a human-approved test-first specification (automated tests plus committed manual test procedures), implementation against frozen tests, automated and human review, history cleanup, and PR.
5 skills · 7 agents
A single-skill lightweight implementation workflow: branch preparation, a requirement discussion with the user, implementation that consults the user whenever it hits a real fork, one human approval gate, then commit, push, and PR. No test freeze, no automated review gate, no Issue registration — but the same VCS minimalism: source code is the only *how*, and every *why* lands in a comment, a commit message, or an ADR.
1 skill
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29 skills · 1 MCP server · hooks
tasteskill 2.5.1: professional company websites at the figma.com and x.ai level, with one section per screen, real photographs, real product UI, effects kept for tech and gaming pages, and a real-browser checker and finish gate.
1 skill
Open-source AI job search that runs locally in your AI coding CLI: scan job portals, evaluate listings into a structured A-H report with a 1-5 score, tailor your CV, track applications
5 skills · hooks
Cross-session memory and token savings for coding agents.
6 skills · 1 agent · 1 MCP server · hooks
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