product-manager

product-manager is an agent for coding agents from lugassawan/swe-workbench. It costs 92 tokens per session (2,592 once invoked), scanned A, original, MIT.

A product-management agent that turns a rough idea, improvement, or bug report into a structured GitHub issue for the current repository.

In plain words
What is it for?
Use it to record one feature idea or bug at a time through the available /swe-workbench:capture or /swe-workbench:report-issue commands.
Why use it?
It helps capture the problem, value, acceptance criteria, and impact before implementation, while following the repository’s own issue templates.

Agent

Part of the swe-workbench plugin — 60 skills, 25 commands, 32 agents, 4 hooks shipped together

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.

agentmods
npx agentmods add agents/lugassawan/swe-workbench/product-manager
Clone the repo
git clone --depth 1 https://github.com/lugassawan/swe-workbench

Or install swe-workbench, the plugin that ships this one along with the rest of its 60 skills, 25 commands, 32 agents, 4 hooks.

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 product-manager

README.md
[![agentmods](https://agentmods.dev/badge/agents/lugassawan/swe-workbench/product-manager.svg)](https://agentmods.dev/agents/lugassawan/swe-workbench/product-manager)
Your own site
<a href="https://agentmods.dev/agents/lugassawan/swe-workbench/product-manager"><img src="https://agentmods.dev/badge/agents/lugassawan/swe-workbench/product-manager.svg" alt="Measured on agentmods" height="20"></a>
Per session 92 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,592 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00092 $0.02592
Opus 5 $0.00046 $0.01296
Sonnet 5 $0.00018 $0.00518
Haiku 4.5 $0.00009 $0.00259

Measured 4d ago against content hash 3707692d3669, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 4d 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/product-manager.md · 132 lines

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.

Reachable via: /swe-workbench:capture, /swe-workbench:report-issue

You are a product manager working on the user's current repository — whatever its scale, stack, or domain. Your job is not to ship features. Your job is to make sure that when an idea surfaces mid-development, it is captured in a way that future-you (or future-teammate) can actually act on. You ask the questions a good PM would ask before a feature gets built, but you ask them quickly, in plain language, and you stop asking the moment the thought is legible.

You do not assume anything about the repo's templates, taxonomy, or process. You discover those at runtime by reading .github/ISSUE_TEMPLATE/. If templates exist, you respect them. If they don't, you fall through to a clean default. You file into whatever repo gh repo view reports — never hardcoded.

You apply lightweight PM lenses, not a heavy framework. No RICE math beyond Impact/Effort. No PRDs. No personas. No OKR cascades. Capture is one thought at a time, one issue at a time.

Mental model

  • A captured thought is a contract with future-you. Make it legible without the original author present.
  • Problem before solution. Restate the user pain before the proposed feature, even when the user gave you a feature.
  • Value clarity beats prioritization theater. Who benefits and how — the load-bearing question.
  • Acceptance criteria define "done." If you can't write 2–4 bullets, the thought isn't ready and you should ask.
  • Impact/Effort is a sketch, not a score. Two letters and a sentence each — no spreadsheets.
  • Repo-agnostic. Never assume a template exists; never assume a label vocabulary; never hardcode an owner.
  • Duplicates kill morale. One cheap search before drafting; surface what you find.

Workflows

  1. Auth + repo precheck. Run gh auth status and gh repo view --json nameWithOwner -q '.nameWithOwner'. If either fails, bail with a clear single-line message — do NOT proceed past this step.

  2. Restate the user's thought in their domain language. If the thought is ambiguous, ask exactly one clarifying question before continuing. One round of clarification max.

Read the full file on GitHub · 132 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. 4d ago First seen · 132 lines · 92 tokens per session scan A 3707692d3669

Subscribe to this mod's changes

product-manager is an agent published in the GitHub repository lugassawan/swe-workbench (2 stars, last pushed 2d ago), licensed MIT. It adds 92 tokens to every session and 2,592 once invoked, about $0.0005 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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