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 rules/zxpmail/reqforge/reqforge-product-specgit clone --depth 1 https://github.com/zxpmail/ReqForgeWhat 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 | $0.00000 | $0.00359 |
| Opus 5 | $0.00000 | $0.00179 |
| Sonnet 5 | $0.00000 | $0.00072 |
| Haiku 4.5 | $0.00000 | $0.00036 |
Grade A, and why
reqforge-product-spec 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 2d 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.
What it actually says
Product Spec Builder
Full skill definition: .cursor/rules/skills/product-spec-builder/SKILL.md
First Principles
- AI-First: For any feature, first consider how it can be done with AI
- Simplicity-First: Complexity is the enemy. Question every feature: "do we really need this?"
- Online-First: WebSearch before recommending competitors, technologies, or solutions
Must Collect (Must Satisfy)
- Product positioning: what is it? What problem does it solve?
- Target users: who will use it? Why?
- Core features: what must it have? What makes the product invalid if removed?
- User flow: complete path from opening to task completion
- AI capability needs: which features need AI? What type?
- Product type: Web / Desktop / CLI / Mobile
Questioning Strategy
- Only 1-2 questions at a time, make them count
- Do not accept vague answers: "roughly", "maybe", "probably"
- Spot logical flaws and point them out directly
- When the user says "you decide", analyze and recommend then ask for confirmation
- Proactively suggest AI enhancement: "should we add a one-click AI X here?"
Output: Product-Spec.md
Use .cursor/rules/skills/product-spec-builder/templates/product-spec-template.md for format.
Final validation loop: scan for redundancy/contradiction/vagueness → auto-fix → re-scan until clean → present remaining issues for user confirmation.
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.
- 2d ago First seen · 34 lines · 0 tokens per session scan A eb34108c00ea
reqforge-product-spec is a cursor rule published in the GitHub repository zxpmail/ReqForge (18 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 359 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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