Spec-driven autonomous development pipeline: author a master spec, decompose into phases, execute each phase under TDD with deterministic specpipe validator gates (structure, dependency graphs, decision-id citations, TDD step order, RED/GREEN evidence, round caps) in front of every review pass.
Plugin spec-pipeline from marketplace l3digitalnet-plugins in L3DigitalNet/Claude-Code-Plugins. Commands read from the repo's manifest — 1 month ago.
authorAuthor the canonical project spec and decompose it into phases for execution by /spec-pipeline:execute-phase. Run once at project inception.
execute-phaseExecute the next pending phase of the named project end-to-end — derive the phase spec from the master, plan it, implement under TDD with review gates, and update handoff state. Run once per phase, passing the project name.
/spec-pipeline:init-projectScaffold the minimal spec-pipeline handoff layout (phase-plan, audit dir, gitignore entry)
/spec-pipeline:statusRender the spec-pipeline phase plan — statuses, next pending phase, review-round counters
/spec-pipeline:validateRun spec-pipeline structural validators against a spec, plan, or phase-plan file
Comprehensive Home Assistant integration development toolkit with 27 skills, MCP server for live HA connection, automated validation, example integrations, and project templates
27 skills · 2 commands · 3 agents · 1 MCP server · hooks
Qt development and testing toolkit: proactive specialist agents, 16 domain references, scaffolding commands, and headless GUI testing via Qt Pilot MCP for PySide6, PyQt6, and C++/Qt projects.
6 commands · 6 agents · 1 MCP server
Update documentation across three layers (repo, llm-wiki, Notion) via sub-agent propagation plus drift audit, all on Sonnet. Five commands for targeted updates and comprehensive drift analysis with four-phase convergence.
5 skills · 4 agents · hooks
Python Tooling SSOT Standard: uv + Ruff + BasedPyright (strict) + pytest/coverage + pip-audit. Operationalizes a single, strict, boring toolchain that behaves identically in CLI, VS Code, and CI. Use when creating Python projects, migrating to uv, auditing conformance, or replacing legacy tooling.
1 skill · hooks · LSP
Deep web research for development decisions: /research dispatches a Sonnet subagent for a dual-source sweep (Tavily-first recall, Brave/Serper cross-checks, Context7 docs gating, footgun corroboration) and persists a structured, frontmatter-indexed report under docs/research/. User-initiated only.
1 command · 1 agent
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