Customise Workflow

customise-workflow

AI-driven workflow customisation for prd-taskmaster-v2. Replaces manual JSON editing.

Script: ~/.claude/skills/prd-taskmaster-v2/companion-skills/customise-workflow/script.py (all commands output JSON)

When to Use

Activate: "customise workflow", "adjust PRD settings", "tune the skill", "change my defaults", "personalise prd-taskmaster". Skip: generating a new PRD (use /prd-taskmaster-v2), executing tasks (use HANDOFF modes).

The One Rule

The AI asks the questions and writes the config. The user never manually edits JSON. The config file is the output, not the input.

Flow

LOAD → ASK → VALIDATE → WRITE → VERIFY

Phase 1: LOAD current config

Run the script to load existing preferences (or defaults if first run):

python3 <skill-dir>/script.py load-config

Returns JSON with current preferences across 6 categories: provider, validation, execution, template, autonomous, gates.

Phase 2: ASK curated questions

Read questions/curated-questions.md and ask each one via AskUserQuestion. The questions are structured so plain-English answers map cleanly to config keys. Example:

Q1: Which AI provider do you prefer for task generation?
  Options: Gemini (free, token-efficient), Claude Code (free, Max only),
           OpenAI GPT-4, Anthropic Direct API, OpenRouter, Ollama (local)

Q2: How strict should PRD validation be?
  Options: Strict (block on NEEDS_WORK), Normal (warn but allow GOOD+),
           Lenient (accept ACCEPTABLE+)

...

Do NOT ask all questions at once. Ask one at a time, adapt follow-ups based on answers. (Same pattern as superpowers:brainstorming.)

Phase 3: VALIDATE answers

Run the script with each user answer as it arrives. The script validates the answer against allowed values and returns either ok: true or a hint about what's wrong.

python3 <skill-dir>/script.py validate-answer --key provider_main --value gemini-cli

Phase 4: WRITE config

After all questions answered, commit the config:

python3 <skill-dir>/script.py write-config --input /tmp/answers.json

This writes to .taskmaster/config/user-workflow.json in the current project. Idempotent — re-running customise-workflow reads and updates the existing file.

Phase 5: VERIFY

Show the user their final config and confirm it matches their intent:

python3 <skill-dir>/script.py show-config

Script Commands Reference

Config Schema

user-workflow.json has 6 top-level keys:

{
  "provider": {
    "main": "gemini-cli|claude-code|anthropic|openai|openrouter|ollama|...",
    "model_main": "gemini-3-pro-preview|sonnet|gpt-4o|...",
    "research": "gemini-cli|perplexity|...",
    "model_research": "sonar-pro|gemini-3-pro-preview|...",
    "fallback": "gemini-cli|claude-code|...",
    "model_fallback": "gemini-3-flash-preview|haiku|..."
  },
  "validation": {
    "strictness": "strict|normal|lenient",
    "ai_review_default": true,
    "min_passing_grade": "EXCELLENT|GOOD|ACCEPTABLE|NEEDS_WORK"
  },
  "execution": {
    "preferred_mode": "A|B|C|D|E|F|G|H|I|J",
    "auto_handoff": true,
    "external_tool": "cursor|codex-cli|gemini-cli|..."
  },
  "template": {
    "default": "comprehensive|minimal",
    "custom_template_path": null
  },
  "autonomous": {
    "allow_self_brainstorm": true,
    "ralph_loop_auto_approve": true
  },
  "gates": {
    "skip_phase_0_if_validated": false,
    "skip_user_approval_in_discovery": false,
    "require_research_expansion": true
  }
}

Phase files read this config at runtime and apply user preferences before falling back to documented defaults.

Critical Rules

1. Never ask the user to edit JSON directly — the skill asks questions and writes the file.
2. Questions are curated and AI-adapted, not a fixed form.
3. Every answer is validated before being written.
4. Config is idempotent — re-running updates cleanly.
5. Config is per-project (lives in .taskmaster/config/), not global.
6. Phase files must GRACEFULLY FALL BACK to documented defaults when config keys are missing.