Borrowing it
Nothing to install: this file belongs to WYRE-AI/autotask-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/WYRE-AI/autotask-mcp/main/.claude/commands/tm/parse-prd/parse-prd.mdgit clone --depth 1 https://github.com/WYRE-AI/autotask-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/wyre-ai/autotask-mcp/parse-prd)<a href="https://agentmods.dev/commands/wyre-ai/autotask-mcp/parse-prd"><img src="https://agentmods.dev/badge/commands/wyre-ai/autotask-mcp/parse-prd.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00235 |
| Opus 5 | $0.00000 | $0.00118 |
| Sonnet 5 | $0.00000 | $0.00047 |
| Haiku 4.5 | $0.00000 | $0.00023 |
Grade A, and why
parse-prd scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
7 near-identical copies found in the catalogue:
What it actually says
Parse a PRD document to generate tasks.
Arguments: $ARGUMENTS (PRD file path)
Intelligent PRD Parsing
Analyzes your requirements document and generates a complete task breakdown.
Execution
task-master parse-prd --input=$ARGUMENTS
Parsing Process
-
Document Analysis
- Extract key requirements
- Identify technical components
- Detect dependencies
- Estimate complexity
-
Task Generation
- Create 10-15 tasks by default
- Include implementation tasks
- Add testing tasks
- Include documentation tasks
- Set logical dependencies
-
Smart Enhancements
- Group related functionality
- Set appropriate priorities
- Add acceptance criteria
- Include test strategies
Options
Parse arguments for modifiers:
- Number after filename →
--num-tasks research→ Use research modecomprehensive→ Generate more tasks
Post-Generation
After parsing:
- Display task summary
- Show dependency graph
- Suggest task expansion for complex items
- Recommend sprint planning
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 49 lines · 0 tokens per session scan A b5b94926d213
parse-prd is a command published in the GitHub repository WYRE-AI/autotask-mcp (50 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 235 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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sprint
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daily-standup
Génération Résumé Daily Stand-up.
create_handoff
Create handoff document for transferring work to another session.
task-management
Query and update recorded planning and research portfolio state across tasks, topics, papers, outputs, submissions, venues, people, institutions, and deadlines. Use when asking what is already recorded, including institution- or venue-associated topics, or when doing daily planning and weekly review. For venue…
parallel
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amby.tasks
Break the plan into an ordered, dependency-aware task checklist.