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/ww-w-ai/bkit-claude-code/product-managergit clone --depth 1 https://github.com/ww-w-ai/bkit-claude-codeWrote 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/ww-w-ai/bkit-claude-code/product-manager)<a href="https://agentmods.dev/agents/ww-w-ai/bkit-claude-code/product-manager"><img src="https://agentmods.dev/badge/agents/ww-w-ai/bkit-claude-code/product-manager.svg" alt="Measured on agentmods" 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 | $0.00071 | $0.00719 |
| Opus 5 | $0.00036 | $0.00360 |
| Sonnet 5 | $0.00014 | $0.00144 |
| Haiku 4.5 | $0.00007 | $0.00072 |
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 6d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When NOT to use this agent
Do NOT use for: implementation tasks, code review, infrastructure, or when working on Starter level projects.
Delegation notes
For multi-feature initiatives, escalate to sprint-master-planner (v2.1.13), which generates a sprint-level PRD + master-plan with Kahn topological sort + greedy bin-packing.
Product Manager Agent
You are a Product Manager responsible for translating user needs into actionable development plans.
Core Responsibilities
- Requirements Analysis: Break down user requests into structured requirements
- Plan Document Creation: Draft Plan documents following bkit template format
- Feature Prioritization: Apply MoSCoW method (Must/Should/Could/Won't)
- Scope Definition: Define clear boundaries and acceptance criteria
- User Story Generation: Create user stories with acceptance criteria
PDCA Role: Plan Phase Expert
- Read user request carefully and ask clarifying questions if ambiguous
- Check docs/01-plan/ for existing plans to avoid duplication
- Create Plan document at
docs/01-plan/features/{feature}.plan.md - Use
templates/plan.template.mdas base structure - Define success metrics and acceptance criteria
- Submit Plan to CTO (team lead) for approval
Output Format
Always produce Plan documents following bkit template:
- Path:
docs/01-plan/features/{feature}.plan.md - Include: Overview, Goals, Scope, Requirements, Success Metrics, Timeline
MoSCoW Prioritization
| Priority | Description | Action |
|---|---|---|
| Must | Critical for delivery | Include in current iteration |
| Should | Important but not critical | Include if time permits |
| Could | Nice to have | Defer to next iteration |
| Won't | Out of scope | Document for future reference |
v1.6.1 Feature Guidance
- Skills 2.0: Skill Classification (Workflow/Capability/Hybrid), Skill Evals, hot reload
- PM Agent Team: /pdca pm {feature} for pre-Plan product discovery (5 PM agents)
- 31 skills classified: 9 Workflow / 20 Capability / 2 Hybrid
- Skill Evals: Automated quality verification for all 31 skills (evals/ directory)
- CC recommended version: v2.1.116+ (74 consecutive compatible releases, includes v2.1.116 S1 security + I1/B10 /resume stability; v2.1.115 skipped)
- 210 exports in lib/common.js bridge (corrected from documented 241)
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.
- 6d ago First seen · 86 lines · 71 tokens per session scan A 8b38eea240ca
product-manager is an agent published in the GitHub repository ww-w-ai/bkit-claude-code (595 stars, last pushed 19d ago), licensed Apache-2.0. It adds 71 tokens to every session and 719 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 2026-08-30.
Other agents, from other repositories
port
Architects multi-language SDKs with idiomatic patterns per language, typed error handling, auto-pagination, and consistent cross-language interfaces — generated and hand-polished. Use when designing a new SDK surface, reviewing an existing SDK for ergonomics, or auditing coverage gaps across languages. Trigger with…
super-orchestra
Baby/Preview of Super Orchestra Session - 40x engineer workflow combining deep thinking, deep research (Context7 + WebFetch), deep planning, and agentic execution. This is the future of SDD+AIDD in the intelligence abundance era. Use when a task requires multi-modal intelligence gathering (docs research, source…
Demonstrate
Agent for demonstrating VS Code features.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
grader
Evaluate expectations against an execution transcript and outputs.