generate
Phase 2 of the prd-taskmaster pipeline: spec generation and task parsing. Loads a template (comprehensive|minimal), fills it with DISCOVER-phase constraints and answers, validates the spec (placeholders_found, grade thresholds), parses the PRD into tasks via task-master, runs TaskMaster's native complexity analysis, and expands every task into verifiable subtasks. Autonomous-safe. Declares GENERATE complete so HANDOFF can follow.
npx skills add anombyte93/prd-taskmaster --skill generate --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Phase 2: Generate Declarative phase skill. Invoked by the prd-taskmaster orchestrator when `current_phase` is `GENERATE`. Never called directly by a user. The one rule: **generate the spec, validate it catches placeholders, parse it into tasks, expand every task into subtasks. Quality over speed.** ## Entry gate 1. Call `mcp__plugin_prd_go__check_gate(phase="GENERATE", evidence={})` for diagnostics. `check_gate` is an EXIT gate: it checks `task_count > 0`, `subtask_coverage >= 1.0`, and `validation_grade in (EXCELLENT, GOOD)` — all of which are GENERATE's OWN OUTPUTS, i.e. evidence to *advance*, not preconditions to *enter*. On first entry none exist yet, so a `gate_passed: false` here is EXPECTED — the state machine's legal transitions 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 from DISCOVER. 2. Read the DISCOVER output (discovery summary + `CONSTRAINTS CAPTURED` block + scale classification). If any of these are missing, report and stop — the gate should have caugh
- Entry gate
- Generate checklist
- Step 1: Choose and load template
- Step 2: Generate spec at .taskmaster/docs/prd.md
- CONSTRAINT CHECK (MANDATORY)
- SCOPE CHECK (MANDATORY)
- Domain-neutral vocabulary
- Deferred decisions — the reason: convention
- Step 3: Validate spec quality
- Step 4: Parse tasks via backend
- Step 5: Rate complexity via backend
- Step 6: Expand tasks into subtasks (MANDATORY)
- Use backend op expand, NOT bare per-id parallel calls
- Patience under slow providers
cat .taskmaster/reports/task-complexity-report.json | jq .
python3 script.py expand
python3 -c "
import json
d = json.load(open('.taskmaster/tasks/tasks.json'))
tasks.json is tag-grouped (master, defaults, feature branches) — walk all tags
all_tasks = []
if 'master' in d and isinstance(d['master'], dict):
all_tasks = d['master'].get('tasks', [])
elif 'tasks' in d:What does the generate skill do?
Phase 2 of the prd-taskmaster pipeline: spec generation and task parsing. Loads a template (comprehensive|minimal), fills it with DISCOVER-phase constraints and answers, validates the spec (placeholders_found, grade thresholds), parses the PRD into tasks via task-master, runs TaskMaster's native complexity analysis, and expands every task into verifiable subtasks. Autonomous-safe. Declares GENERATE complete so HANDOFF can follow.
How do I install it?
Run `npx skills add anombyte93/prd-taskmaster --skill generate --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From anombyte93/prd-taskmaster, a repository with 586 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.