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prd-taskmaster

install
source · Clone the upstream repo
git clone https://github.com/anombyte93/prd-taskmaster
Claude Code · Install into ~/.claude/skills/
git clone --depth=1 https://github.com/anombyte93/prd-taskmaster ~/.claude/skills/anombyte93-prd-taskmaster-prd-taskmaster
manifest: SKILL.md
source content

PRD Generator for TaskMaster v3.0

Smart PRD generation with deterministic operations handled by 

script.py
. AI handles judgment (questions, content, decisions); script handles mechanics.

Script location: 

~/.claude/skills/prd-taskmaster/script.py
All script commands output JSON.

When to Use

Activate when user says: PRD, product requirements, taskmaster, task-driven development. Do NOT activate for: API docs, test specs, project timelines, PDF creation.

Core Principles

  • Quality Over Speed: Planning is 95% of the work
  • Taskmaster Required: Blocks if not detected
  • Engineer-Focused: Technical depth, code examples, architecture
  • Validation-Driven: 13 automated checks via script
  • User Testing Checkpoints: Every 5 tasks

Workflow (12 Steps)

Step 1: Preflight & Resume Detection

python3 ~/.claude/skills/prd-taskmaster/script.py preflight

Returns JSON: 

has_taskmaster
, 
prd_path
, 
task_count
, 
tasks_completed
, 
tasks_pending
, 
taskmaster_method
, 
has_claude_md
, 
has_crash_state
, 
crash_state
.

If 

has_crash_state
is true: Present resume options to user:

  1. Continue from last subtask
  2. Restart current task
  3. Resume from last checkpoint
  4. Start fresh

Then proceed to Step 2.

Step 2: Detect Existing PRD

Use preflight JSON: if 

prd_path
is not null and 
task_count > 0
, an existing PRD is found.

If existing PRD found, use AskUserQuestion:

  • Execute tasks from existing PRD (skip to Step 11)
  • Update/refine existing PRD (edit and re-parse)
  • Create new PRD (replace - backup first via 
    script.py backup-prd --input <path>
    )
  • Review existing PRD (display summary, then exit)

If no PRD found: Proceed to Step 3.

Step 3: Detect Taskmaster

Use preflight JSON field 

taskmaster_method
: 
mcp
, 
cli
, or 
none
.

If 

none
: Block and show installation instructions:

  • Option 1 (recommended): Install MCP Task-Master-AI
  • Option 2: 
    npm install -g task-master-ai
  • Wait for user to install and confirm, then re-run: 
    script.py detect-taskmaster

No proceeding without taskmaster detected.

Step 4: Discovery Questions

Ask detailed questions to build comprehensive PRD. Use AskUserQuestion for structured input.

Essential (5):

  1. What problem does this solve? (user pain point, business impact)
  2. Who is the target user/audience?
  3. What is the proposed solution or feature?
  4. What are the key success metrics?
  5. What constraints exist? (technical, timeline, resources)

Technical (4): 6. Existing codebase or greenfield? 7. Tech stack? 8. Integration requirements? 9. Performance/scale requirements?

TaskMaster-specific (3): 10. Used taskmaster before? 11. Estimated complexity? (simple/typical/complex) 12. Timeline expectations?

Open-ended (1): 13. Anything else? (edge cases, constraints, context)

Smart defaults: If user provides minimal answers, use best guesses and document assumptions.

Step 5: Initialize Taskmaster

Only if 

.taskmaster/
doesn't exist (check preflight 
has_taskmaster
).

python3 ~/.claude/skills/prd-taskmaster/script.py init-taskmaster --method <cli|mcp>

For MCP: use the returned params to call 

mcp__task-master-ai__initialize_project
. For CLI: script runs 
taskmaster init
directly.

Step 6: Generate PRD

Load template:

python3 ~/.claude/skills/prd-taskmaster/script.py load-template --type <comprehensive|minimal>

Returns JSON with 

content
field containing the template.

AI judgment: Fill template with user's answers from Step 4:

  • Replace placeholders with actual content
  • Expand examples with project-specific details
  • Add technical depth based on discovery answers

Write completed PRD to 

.taskmaster/docs/prd.md
.

Step 7: Validate PRD Quality

python3 ~/.claude/skills/prd-taskmaster/script.py validate-prd --input .taskmaster/docs/prd.md

Returns JSON: 

score
, 
max_score
, 
grade
, 
checks
(13 items), 
warnings
.

Grading: EXCELLENT (91%+), GOOD (83-90%), ACCEPTABLE (75-82%), NEEDS_WORK (<75%).

AI judgment: If warnings exist, offer user three options:

  1. Proceed with current PRD
  2. Auto-fix warnings
  3. Review and fix manually

If grade is NEEDS_WORK, strongly recommend fixing before proceeding.

Step 8: Parse & Expand Tasks

Calculate task count:

python3 ~/.claude/skills/prd-taskmaster/script.py calc-tasks --requirements <count>

Returns 

recommended
task count.

For MCP:

mcp__task-master-ai__parse_prd: input=".taskmaster/docs/prd.md", numTasks=<recommended>, research=true
mcp__task-master-ai__expand_all: research=true

For CLI:

taskmaster parse-prd --input .taskmaster/docs/prd.md --research --num-tasks <recommended>
taskmaster expand-all --research

Step 9: Insert User Test Tasks

python3 ~/.claude/skills/prd-taskmaster/script.py gen-test-tasks --total <task_count>

Returns array of USER-TEST task definitions with 

title
, 
description
, 
dependencies
, 
template
.

For each task in the array:

  • MCP: 
    mcp__task-master-ai__add_task
    with title, description, details=template, dependencies, priority=high
  • CLI: 
    taskmaster add-task --title="..." --description="..." --dependencies="..." --priority=high

Step 10: Setup Tracking Scripts

python3 ~/.claude/skills/prd-taskmaster/script.py gen-scripts --output-dir .taskmaster/scripts

Creates 5 scripts: track-time.py, rollback.sh, learn-accuracy.py, security-audit.py, execution-state.py.

Step 10.5: Generate CLAUDE.md

Pre-check: Use Glob to check if 

./CLAUDE.md
exists. If it exists, skip.

If generating:

  1. Load template: 
    script.py load-template
    won't work here -- use Read tool on 
    ~/.claude/skills/prd-taskmaster/templates/CLAUDE.md.template
  2. AI judgment: Replace placeholders with project-specific values from discovery: 
    • {{PROJECT_NAME}}
      , 
      {{TECH_STACK}}
      , 
      {{ARCHITECTURE_OVERVIEW}}
    • {{KEY_DEPENDENCIES}}
      , 
      {{TESTING_FRAMEWORK}}
      , 
      {{DEV_ENVIRONMENT}}
      , 
      {{TEST_COMMAND}}
  3. Write to 
    ./CLAUDE.md
  4. Ask if user uses Codex -- if yes and no 
    codex.md
    , write identical copy

Step 11: Choose Next Action

Use AskUserQuestion:

Question: "PRD and tasks ready. How to proceed?"

  • Show TaskMaster Commands (default): Display command reference, then exit skill
  • Autonomous Execution: Ask follow-up for execution mode

If Autonomous Execution selected, ask execution mode:

  • Sequential to Checkpoint (recommended): Tasks one-by-one until next USER-TEST
  • Parallel to Checkpoint: Independent tasks in parallel until USER-TEST
  • Full Autonomous: All tasks parallel, skip user validation
  • Manual Control: User decides each task

AI judgment: Recommend mode based on context:

  • First-time/critical: Sequential
  • Experienced/non-critical: Parallel
  • Trusted/time-critical: Full Autonomous
  • Complex/learning: Manual

Step 12: Summary & Start

If Handoff: Display PRD location, task counts, key requirements, validation score, task phases, user test checkpoints, and TaskMaster commands. Then exit skill.

If Autonomous: Display same summary plus execution mode, then begin execution using the selected mode's rules.

Execution Mode Rules

All Modes Include

  • DateTime tracking: 
    python3 .taskmaster/scripts/track-time.py start|complete <task_id> [subtask_id]
  • Progress logging: 
    python3 ~/.claude/skills/prd-taskmaster/script.py log-progress --task-id <id> --title "..." --duration "..." --subtasks "..." --tests "..." --issues "..."
  • Git policy: Branch per task (
    task-{id}-{slug}
    ), sub-branch per subtask, merge to main with checkpoint tag
  • Rollback: If user says "rollback to task X", run 
    bash .taskmaster/scripts/rollback.sh X
  • State tracking: 
    python3 .taskmaster/scripts/execution-state.py start|complete|checkpoint <task_id>

Sequential to Checkpoint

Execute tasks one-by-one. For each task:

  1. Start time tracking
  2. Create feature branch
  3. For each subtask: create sub-branch, implement, test, commit, merge to task branch
  4. Complete time tracking
  5. Log progress
  6. Merge to main, create checkpoint tag
  7. Stop at next USER-TEST for user validation

Parallel to Checkpoint

Same as sequential but launch up to 3 concurrent independent tasks. Handle merge conflicts automatically. Stop at USER-TEST.

Full Autonomous

Maximum parallelization (up to 5 concurrent). Auto-complete USER-TEST tasks. Only stop when ALL tasks complete.

Manual Control

Wait for user commands: "next task", "task {id}", "status", "parallel {id1,id2}".

Tips

  • More detail in discovery = better PRD
  • Quantify goals: not "improve UX" but "increase NPS from 45 to 60"
  • USER-TEST checkpoints catch issues early
  • Git checkpoints allow easy rollback
  • Use 
    script.py validate-prd
    at any time to re-check PRD quality