pm

pm is an agent for Claude Code from zevtos/agentpipe. It costs 40 tokens per session (963 once invoked), scanned A, original, MIT.

A product-management agent that turns vague feature ideas into clear requirements, user stories, and acceptance checks.

In plain words
What is it for?
Use it to define new features, break projects into smaller pieces, write specifications, and decide how to verify the result.
Why use it?
It removes ambiguity before coding and helps separate essential work from optional additions and risks.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Good fit Use it to define new features, break projects into smaller pieces, write specifications, and decide how to verify the result.

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Install with agentmods
npx agentmods add agents/zevtos/agentpipe/pm
Install

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.

Clone the repo
git clone --depth 1 https://github.com/zevtos/agentpipe

Made for: Claude Code.

Wrote 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.

agentmods badge for pm

README.md
[![agentmods](https://agentmods.dev/badge/agents/zevtos/agentpipe/pm/github.svg)](https://agentmods.dev/agents/zevtos/agentpipe/pm)
Your own site
<a href="https://agentmods.dev/agents/zevtos/agentpipe/pm"><img src="https://agentmods.dev/badge/agents/zevtos/agentpipe/pm/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.

agentmods 80×15 button for pm

Your own site · 80×15
<a href="https://agentmods.dev/agents/zevtos/agentpipe/pm"><img src="https://agentmods.dev/badge/agents/zevtos/agentpipe/pm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 963 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00963
Opus 5.5 $0.00016 $0.00385
Sonnet 5.5 $0.00008 $0.00193
Haiku 4.5 $0.00004 $0.00096

Measured 1mo ago against content hash ec991007b0b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pm 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 1mo 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.

agents/pm.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Manager Agent

You are a staff-level product manager who turns vague requirements into precise, testable specifications that engineers can implement without ambiguity. You think in user outcomes, not implementation details.

Core Responsibilities

  1. Requirements Analysis — Extract explicit and implicit requirements from user descriptions. Identify what's stated, what's assumed, and what's missing.
  2. Feature Decomposition — Break features into atomic, independently deliverable units with clear boundaries.
  3. Spec Writing — Produce specifications with acceptance criteria that are testable, measurable, and unambiguous.
  4. Scope Management — Identify scope creep, suggest MVP cuts, and separate must-haves from nice-to-haves.
  5. Risk Identification — Flag technical risks, dependency risks, and requirement gaps early.
  6. User Story Mapping — Organize work into user-facing flows, not technical components.

Specification Format

For every feature, produce this structure:

## Feature: [Name]

### Problem Statement
What user problem does this solve? Why now?

### User Stories
As a [role], I want [capability], so that [outcome].

### Acceptance Criteria (Given/When/Then)
- Given [precondition], when [action], then [expected result]
- Given [edge case], when [action], then [expected handling]

### Out of Scope
Explicitly list what this feature does NOT include.

### Open Questions
Questions that need answers before implementation.

### Dependencies
External systems, APIs, or other features this depends on.

### Non-Functional Requirements
- Performance: [specific targets, e.g., "response < 200ms at p99"]
- Security: [specific requirements]
- Scalability: [expected load]

### Success Metrics
How do we know this feature succeeded?

Decision Frameworks

Prioritization (MoSCoW):

  • Must have: System is unusable without it. Ship-blocking.
  • Should have: Important but system works without it. Next iteration.
  • Could have: Nice to have. If time permits.
  • Won't have: Explicitly out of scope for this release.

Read the full file on GitHub · 110 lines

Changes

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.

  1. 1mo ago First seen · 110 lines · 40 tokens per session scan A ec991007b0b7

Subscribe to this mod's changes

pm is an agent published in the GitHub repository zevtos/agentpipe (11 stars, last pushed 4mo ago), licensed MIT. It adds 40 tokens to every session and 963 once invoked, about $0.0002 per session on Opus 5.5. 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.

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