agentsclimarketplace

Setup

Skill anombyte93/prd-taskmaster/skills/setup

Zero-config goal-to-tasks engine for Claude Code (the Atlas engine). Graded PRD validation, dependency-ordered task graph, evidence-gated execution.

Install
npx -y skills add anombyte93/prd-taskmaster --skill setup

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

What its author says it does

Copied from the file, not written here

Phase 0 of the prd-taskmaster pipeline. Resolves the active backend, initializes the project, configures the provider stack when the TaskMaster backend is active (DETECT-FIRST — never overwrite a working user config), and verifies the AI pipeline. Autonomous: zero user questions unless a hard block is hit. Declares the Setup phase complete so DISCOVER can follow.

SKILL.md

7.4 KB, as published. Nobody here has run it

Phase 0: Setup

Declarative phase skill. Invoked by the prd-taskmaster orchestrator when current_phase is null or SETUP. Never called directly by a user.

Entry gate

  1. Call mcp__plugin_prd_go__check_gate(phase="SETUP", evidence={}) for diagnostics.

    check_gate is an EXIT gate: it verifies you have the evidence to advance, not to enter. On first entry you have no evidence yet (Step 4 below produces validate_setup.ready=true), so a gate_passed: false result here is EXPECTED — the state machine's legal transitions (None → SETUP) already guarantee only legal entry.

    • First entry (no evidence yet): note the result and continue with the Procedure.
    • Re-entry: if the gate reports violations, report them and stop — it protects against re-running a completed phase or skipping ahead.

    Enforce the gate when you ADVANCE (after the procedure), not on entry.

Procedure (5 steps, abort on hard failure)

Step 1: Backend detection

Run backend detection:

python3 script.py backend-detect

The native engine is the sole generator and needs no external binary — a keyless host CLI (claude / codex / gemini) on PATH, or a provider API key, is sufficient (see Chunk 7's atlas setup wizard). The task-master binary is no longer required or supported; backend-detect reports its presence purely as informational. Continue with the resolved (native) backend.

Step 2: Project init

Check whether the current project has a .taskmaster/ directory (the engine still reads/writes the .taskmaster/ file format for tasks and config).

If missing, run backend op init:

python3 script.py init-project

This initialises the native project state and the .taskmaster/ file format. If .taskmaster/ is present, continue.

Step 2.5: Customisation bootstrap (REQUIRED — closes execute-task deadlock)

execute-task requires .atlas-ai/customizations/system-prompt-template.md to exist as a precondition (its Entry gate halts otherwise). It cannot create the file from inside the loop — the failure mode is a hard halt with no recovery path.

This step ensures the file exists BEFORE execute-task ever runs:

PLUGIN_SKEL="${CLAUDE_PLUGIN_ROOT}/skel/customizations"
mkdir -p .atlas-ai/customizations
if [ ! -f .atlas-ai/customizations/system-prompt-template.md ]; then
  if [ -d "$PLUGIN_SKEL" ]; then
    cp -n "$PLUGIN_SKEL"/*.md .atlas-ai/customizations/  # -n: no-clobber, copy starter pack
  else
    : > .atlas-ai/customizations/system-prompt-template.md  # empty is fine per execute-task Entry gate
  fi
fi

The starter pack (domain-vocabulary.md, system-prompt-template.md, task-enrichment-rules.md, verification-preferences.md) is editable — users tune them to project-specific terminology. Empty is acceptable; the file simply must exist.

Also scaffold .atlas-ai/ship-check.py if it doesn't already exist:

if [ ! -f .atlas-ai/ship-check.py ] && [ -f "${CLAUDE_PLUGIN_ROOT}/skel/ship-check.py" ]; then
  cp "${CLAUDE_PLUGIN_ROOT}/skel/ship-check.py" .atlas-ai/ship-check.py
  chmod +x .atlas-ai/ship-check.py
fi

(Codified 2026-06-04 — yesterday's run halted at execute-task Entry because system-prompt-template.md was missing; the file had to be manually touch-ed from outside the loop.)

Step 3: Provider configuration — DETECT-FIRST

When the TaskMaster backend is active, read task-master models output BEFORE setting anything. This is the load-bearing rule. A working user config must NOT be overwritten silently. When the native backend is active, provider configuration is handled by the resolved backend and this TaskMaster-specific step is informational only.

task-master models outputAction
Main / Research / Fallback all populated with a supported providerSKIP — go to Step 4.
Main set, Research/Fallback emptyPartial mutate — fill the empty roles only.
All three empty (fresh install)Full configure — use the default stack below.
Provider flagged unsupported / deprecatedAsk the user before mutating.

Why DETECT-FIRST: v4 dogfood (2026-04-13, LEARNING #9) caught the skill overwriting a working gemini-cli / gemini-3-pro-preview config because the procedure wasn't branch-aware. Detect first, mutate only the empty slots.

Default stack (fresh install only):

task-master models --set-main gemini-3-pro-preview --gemini-cli
task-master models --set-research gemini-3-pro-preview --gemini-cli
task-master models --set-fallback gemini-3-flash-preview --gemini-cli

Why Gemini CLI: ~113× more token-efficient than sonnet on parse-prd, free via any Google account, no API key. One provider, three roles, zero cost.

Alternatives: Claude Max (--claude-code sonnet/opus/haiku), any of the 12 task-master provider families, or a registered MCP research tool for the Research role.

Step 4: Probe test

If tasks already exist, call the MCP tool mcp__plugin_prd_go__validate_setup or run backend op rate:

python3 script.py rate

If no tasks exist yet (fresh project), skip the probe — Step 3's provider configuration is sufficient evidence the pipeline is wired.

Step 5: Status line

Render the preflight progress panel and print it. MCP-mode: call render_status(phase="SETUP") and print its rendered field. CLI-mode: python3 script.py status --phase SETUP. (Fallback if the renderer is unavailable — emit a compact one-block status:)

Setup:
  task-master: installed (<version>)
  project: initialized (.taskmaster/)
  provider: <main-provider> (main) / <research-provider> (research)
  pipeline: verified

Exit gate

After Steps 1–5 report green:

  1. Call mcp__plugin_prd_go__advance_phase(expected_current="SETUP", target="DISCOVER", evidence={"validate_setup": <Step 4 result dict>, "provider_configured": True}). The call atomically transitions pipeline.json from SETUP to DISCOVER. The expected_current field is the compare-and-swap guard; evidence is stored under phase_evidence[DISCOVER] for audit.
  2. Return control to the orchestrator (prd-taskmaster skill). Do NOT invoke DISCOVER directly — the orchestrator re-reads current_phase and routes.

Red flags (stop and report, do not paper over)

  • "The config is set but looks wrong — I'll fix it" → NO. Report and ask.
  • "No tasks exist so I'll skip backend detection" → NO. Backend detection must run before DISCOVER so later backend ops resolve consistently.
  • "I'll auto-install task-master via npm" → NO. Installation is a user action; this skill only reports that installation unlocks the TaskMaster backend.
  • "I can call advance_phase without check_gate" → NO. Gate first, always.

Non-exits

This skill does not use explicit process termination. A hard block reports the reason and returns control to the orchestrator; the orchestrator decides whether to surface to the user.

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.