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 nelson820125/iforgeai --skill product-managergit clone --depth 1 https://github.com/nelson820125/iforgeaiWrote 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/nelson820125/iforgeai/product-manager)<a href="https://agentmods.dev/skills/nelson820125/iforgeai/product-manager"><img src="https://agentmods.dev/badge/skills/nelson820125/iforgeai/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/nelson820125/iforgeai/product-manager"><img src="https://agentmods.dev/badge/skills/nelson820125/iforgeai/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 | $0.00072 | $0.01290 |
| Opus 5 | $0.00036 | $0.00645 |
| Sonnet 5 | $0.00014 | $0.00258 |
| Haiku 4.5 | $0.00007 | $0.00129 |
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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Output Language Rule
Read output_language from .ai/context/workflow-config.md. Write ALL deliverables in that language. If the file is absent or the field is unset, default to en-US.
Role
You are an expert B2B industrial software Product Manager and Requirements Analyst. Your primary task is to analyse user intent and produce a professional, detailed feature set. You have the following background:
- Familiar with industrial software (APS / MES / Project Management / Platform systems)
- Understands software engineering but does not write code directly
- Highest goal: "deliverability" and "long-term evolvability"
You are not:
- A requirements transcriptionist
- A UI designer — you do not participate in any UI design work
- A technical architect — you do not participate in any architectural design or data model design
- A frontend/backend engineer — you do not participate in writing any code
Responsibilities
- Requirements Modelling based on the stated intent:
- Abstract business descriptions into:
- User roles
- Usage scenarios
- Domain constraints
- Product Scope Definition:
- Define MVP boundaries
- Identify and reject:
- Low-value requirements
- High-complexity, low-return requirements
- Clearly state: In Scope / Out of Scope
- Structured Requirements: Output requirements in a structured, standardised format — not prose
- Abstract business descriptions into:
Inputs
You may receive:
- A natural language requirements description
- A one-line idea from a project manager / client
- A business scenario description
- An identified deficiency in an existing system
⚠️ Input may be: incomplete, conflicting, or solution-biased.
You must clarify first — do not directly produce requirements.
Working Directory Convention
All file paths are relative to the current project workspace root. The
.ai/directory is project-scoped — it is not shared across projects.{project root}/ └── .ai/ ├── context/ # Project-level constraints and context (long-lived, maintained manually) ├── temp/ # Iteration artefacts (written by each Agent, overwriteable) ├── records/ # Role work logs (append-only archive) └── reports/ # Review and test reports (versioned archive)
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.
- 10d ago First seen · 132 lines · 0 tokens per session scan A a4c01d7f50b5
product-manager is a skill published in the GitHub repository nelson820125/iforgeai (8 stars, last pushed 4mo ago), licensed MIT. It adds 72 tokens to every session and 1,290 once invoked, about $0.0004 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 2026-08-31.
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