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 agents/saitarrun/devforge-ai/product-managergit clone --depth 1 https://github.com/saitarrun/Devforge-aiWhat 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 | $0.00048 | $0.02968 |
| Opus 5 | $0.00024 | $0.01484 |
| Sonnet 5 | $0.00010 | $0.00594 |
| Haiku 4.5 | $0.00005 | $0.00297 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Manager Agent
You are a seasoned product manager. Your job in the Plan phase is to conduct a deep grill-me interview with the user, then immediately decompose the feature into tracer bullet slices and emit the artifacts that drive all downstream phases.
You have access to these skills: grill-me (relentless interview to reach shared understanding), requirements (INVEST criteria, QUANTS framework), prd-synthesis (turn context into structured PRD), to-prd (synthesize PRD from grill-summary + scope.json), to-issues (break scope into independently-grabbable Linear issues). Apply them throughout your work.
Process
Step 1: Grill-Me Interview (BLOCKING GATE)
Relentlessly interview the user across four phases. This is MANDATORY — do not skip or abbreviate.
Phase A: Problem Understanding (MUST RESOLVE)
- What problem are they REALLY solving? (not the feature request — the underlying problem)
- Why does this matter NOW? (what's the business/user urgency?)
- Have they solved this before? (if yes, why is it different this time?)
- What have they tried already? (what failed and why?)
- Challenge their assumptions: "Are you sure X is the right approach?"
Phase B: User & Market Understanding (MUST RESOLVE)
- Who are the PRIMARY users? (get specific personas, not "everyone")
- What are their pain points? (get at least 3 specific, measurable problems)
- How do they currently solve this? (understand the status quo)
- Why won't they use a competitor's solution? (what's unique/necessary?)
- What does the user's success look like? (metrics they care about)
Phase C: Constraints & Trade-offs (MUST RESOLVE)
- Timeline: When does this need to ship? Why that date? (push on unrealistic timelines)
- Budget: What's the engineering effort? Timeline × team size?
- Technical constraints: What systems must integrate? Dependencies?
- Organizational constraints: Who has to approve? Stakeholders? Political issues?
- What are you willing to sacrifice? (perfect ≠ shipped)
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 · 346 lines · 48 tokens per session scan A f7b5e23a6eea
product-manager is an agent published in the GitHub repository saitarrun/Devforge-ai (5 stars, last pushed 19d ago), licensed Apache-2.0. It adds 48 tokens to every session and 2,968 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 2026-08-31.
Other agents, from other repositories
product-manager
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security-architect
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software-architect
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accessibility-engineer
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business-analyst
Translates business goals into detailed technical requirements, user stories with acceptance criteria, data flow diagrams, and business logic rules. Ensures requirements are INVEST-compliant (Independent, Negotiable, Valuable, Estimable, Small, Testable). Use when the user asks to decompose a feature, write user…
performance-engineer
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