Setup

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.

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.