Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/jnarowski/agentcmd/generate-prdgit clone --depth 1 https://github.com/jnarowski/agentcmdWhat 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 | $0.00012 | $0.02536 |
| Opus 5 | $0.00006 | $0.01268 |
| Sonnet 5 | $0.00002 | $0.00507 |
| Haiku 4.5 | $0.00001 | $0.00254 |
Grade A, and why
generate-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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Requirements Document (PRD)
Generate high-level PRD focusing on "what" and "why" before implementation. Creates folder at .agent/specs/todo/[id]-[feature]/prd.md with timestamp-based ID.
Variables
- $param1: $1 (optional) - Feature context or description (infers from conversation if omitted)
Instructions
- IMPORTANT: Use your reasoning model - THINK HARD about feature requirements, user needs, and business value
- IMPORTANT: This command ONLY generates the PRD - do NOT implement any code or make file changes beyond creating the folder/file and updating index.json
- Normalize feature name to kebab-case for the folder name
- Replace ALL
<placeholders>with specific details relevant to that section - Focus on WHAT and WHY, not HOW (save implementation details for spec)
- Keep it high-level but comprehensive
- DO NOT include implementation tasks or complexity scores - this is for planning only
Workflow
-
Determine Context:
- If $param1 provided: Use as context
- If $param1 empty: Infer from conversation history
-
Generate Spec ID:
- Generate timestamp-based ID in format
YYMMDDHHmmusing current local time - Example: November 13, 2025 at 3:22pm local →
2511131522 - Read
.agent/specs/index.json(will be updated in step 8)
- Generate timestamp-based ID in format
-
Generate Feature Name:
- Generate concise kebab-case name from context (max 4 words)
- Examples: "Add OAuth support" → "oauth-support", "Dashboard redesign" → "dashboard-redesign"
-
Research Phase:
- Research codebase for existing patterns relevant to the feature
- Gather context about architecture, file structure, and conventions
- Look for similar features for inspiration
-
Clarification (conditional):
- If explicit context provided: Resolve ambiguities autonomously using recommended best practices
- If inferring from conversation: Ask clarifying questions ONE AT A TIME if requirements are unclear:
- Don't use the Question tool
- Use this template:
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.
- today First seen · 312 lines · 12 tokens per session scan A 9737d99d6aae
generate-prd is a command published in the GitHub repository jnarowski/agentcmd (18 stars, last pushed 8mo ago), licensed MIT. It adds 12 tokens to every session and 2,536 once invoked, about $0.0001 per session on Opus 5. 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 2026-09-01.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.