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 skills add vikisingh23/neuraforge-ai --skill product-managergit clone --depth 1 https://github.com/vikisingh23/neuraforge-aiWrote 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/skills/vikisingh23/neuraforge-ai/product-manager)<a href="https://agentmods.dev/skills/vikisingh23/neuraforge-ai/product-manager"><img src="https://agentmods.dev/badge/skills/vikisingh23/neuraforge-ai/product-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vikisingh23/neuraforge-ai/product-manager"><img src="https://agentmods.dev/badge/skills/vikisingh23/neuraforge-ai/product-manager.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.00358 |
| Opus 5 | $0.00016 | $0.00179 |
| Sonnet 5 | $0.00006 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
product-manager 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 8d 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
Create business requirements, PRDs with embedded Figma screen workflows, and user stories.
How to use
Describe a feature in plain English. The agent creates:
- BRS with acceptance criteria
- PRD document (.docx) — text-only or merged with Figma screenshots
- User stories with story points
- Edge cases and error scenarios
- Domain-aware: adapts to your configured industry/regulations
PRD Generation Modes
- Text-only PRD —
generate prd for [feature]— produces .docx with all sections, no screenshots - PRD + Figma screens —
generate prd for [feature] with figma [url]— fetches individual screens from Figma, exports PNGs, embeds them inline with component specs, props, Figma links, and a traceability matrix
Figma Integration
When a Figma URL is provided:
- Extracts section children (individual screen frames)
- Classifies as Web (≥1200px) or Mobile (<500px)
- Exports each as PNG
- Embeds in document with: screenshot, component name, route, props, API calls, Figma deep link
- Generates traceability matrix (Screen ↔ PRD Section ↔ Acceptance Criteria)
For full instructions, read agents/product-manager.md.
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.
- 8d ago First seen · 36 lines · 32 tokens per session scan A 49c3484303d8
product-manager is a skill published in the GitHub repository vikisingh23/neuraforge-ai (4 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 358 once invoked, about $0.0002 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 2026-09-03.
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