agentsclimarketplace

Speckit plan

Skill h3y6e/speckit-skills/skills/speckit-plan

Packaged github/spec-kit as portable Agent Skills

Install
npx -y skills add h3y6e/speckit-skills --skill speckit-plan

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Generate technical implementation plans from feature specifications. Use after creating a spec to define architecture, tech stack, and implementation phases. Creates plan.md with detailed technical design.

SKILL.md

3.1 KB, as published. Nobody here has run it

Speckit Plan Skill

Outline

  1. Setup: Run scripts/setup-plan.sh --json from repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").

  2. Load context: Read FEATURE_SPEC and specs/constitution.md. Load IMPL_PLAN template (already copied).

  3. Execute plan workflow: Follow the structure in IMPL_PLAN template to:

    • Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
    • Fill Constitution Check section from constitution
    • Evaluate gates (ERROR if violations unjustified)
    • Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
    • Phase 1: Generate data-model.md, contracts/, quickstart.md
    • Phase 1: Update agent context by running the agent script
    • Re-evaluate Constitution Check post-design

  4. Stop and report: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.

Phases

Phase 0: Outline & Research

  1. Extract unknowns from Technical Context above:

    • For each NEEDS CLARIFICATION → research task
    • For each dependency → best practices task
    • For each integration → patterns task

  2. Generate and dispatch research agents:

    For each unknown in Technical Context:
  Task: "Research {unknown} for {feature context}"
For each technology choice:
  Task: "Find best practices for {tech} in {domain}"

  3. Consolidate findings in research.md using format:

    • Decision: [what was chosen]
    • Rationale: [why chosen]
    • Alternatives considered: [what else evaluated]

Output: research.md with all NEEDS CLARIFICATION resolved

Phase 1: Design & Contracts

Prerequisites: research.md complete

  1. Extract entities from feature spec → data-model.md:

    • Entity name, fields, relationships
    • Validation rules from requirements
    • State transitions if applicable

  2. Define interface contracts (if project has external interfaces) → /contracts/:

    • Identify what interfaces the project exposes to users or other systems
    • Document the contract format appropriate for the project type
    • Examples: public APIs for libraries, command schemas for CLI tools, endpoints for web services, grammars for parsers, UI contracts for applications
    • Skip if project is purely internal (build scripts, one-off tools, etc.)

  3. Agent context update:

    • Run scripts/update-agent-context.sh codex
    • These scripts detect which AI agent is in use
    • Update the appropriate agent-specific context file
    • Add only new technology from current plan
    • Preserve manual additions between markers

Output: data-model.md, /contracts/*, quickstart.md, agent-specific file

Key rules

  • Use absolute paths
  • ERROR on gate failures or unresolved clarifications

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.