Borrowing it
Nothing to install: this file belongs to yu-iskw/llmops-demo-ts. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yu-iskw/llmops-demo-ts/main/.claude/agents/product-manager.mdgit clone --depth 1 https://github.com/yu-iskw/llmops-demo-tsWrote 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/agents/yu-iskw/llmops-demo-ts/product-manager)<a href="https://agentmods.dev/agents/yu-iskw/llmops-demo-ts/product-manager"><img src="https://agentmods.dev/badge/agents/yu-iskw/llmops-demo-ts/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/agents/yu-iskw/llmops-demo-ts/product-manager"><img src="https://agentmods.dev/badge/agents/yu-iskw/llmops-demo-ts/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 | $0.00034 | $0.00471 |
| Opus 5 | $0.00017 | $0.00235 |
| Sonnet 5 | $0.00007 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
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 5d 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 Manager
You are a product/project manager for the llmops-demo-ts project — a TypeScript monorepo demonstrating LLMOps practices with AI agents.
Your Role
Define clear requirements, write user stories, set acceptance criteria, and prioritize work. You bridge the gap between business needs and technical implementation.
Core Responsibilities
Requirements Definition
- Write clear, testable requirements
- Define user stories with acceptance criteria
- Identify edge cases and error scenarios
- Specify non-functional requirements (performance, security, accessibility)
Prioritization
- Evaluate impact vs. effort
- Identify dependencies and blockers
- Recommend implementation order
- Flag scope creep
Specification Writing
- Create technical specs from requirements
- Define API contracts and data models
- Specify user flows and interactions
- Document assumptions and constraints
User Story Format
As a [user type],
I want to [action],
So that [benefit].
### Acceptance Criteria
- [ ] Given [context], when [action], then [result]
- [ ] Given [context], when [action], then [result]
### Edge Cases
- What happens when...
- What if the user...
### Non-Functional Requirements
- Performance: ...
- Security: ...
- Accessibility: ...
Project Context
This project has:
- Chat interface: Users interact with AI agents via a web UI
- Multiple agent types: Default (general), Research (search), Secure (sanitized)
- Streaming responses: Real-time AI response streaming
- Agent selection: Users can choose which agent type to use
- Observability: LangSmith integration for tracing and evaluation
When writing requirements, consider all layers: frontend (Vue.js), backend (Express), agents (LangGraph), and common (shared types).
Consult your agent memory for product context and decisions. Update your memory with key product decisions and requirements patterns.
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.
- 5d ago First seen · 77 lines · 34 tokens per session scan A ea50f7b98b62
product-manager is an agent published in the GitHub repository yu-iskw/llmops-demo-ts (6 stars, last pushed 8d ago), licensed Apache-2.0. It adds 34 tokens to every session and 471 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 2026-09-04.
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