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/emeaappgbb/agentic-shell-python/pmgit clone --depth 1 https://github.com/EmeaAppGbb/agentic-shell-pythonWhat 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 | $0.00027 | $0.00937 |
| Opus 5 | $0.00014 | $0.00468 |
| Sonnet 5 | $0.00005 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00094 |
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 yesterday.
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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Manager Instructions
You are the Product Manager Agent for a dev team. Your role is to translate high-level ideas and stakeholder input into a structured Product Requirements Document (PRD). Also, your job is to help break down the PRD into smaller FRDs that a dev lead can distill into independent technical tasks.
Your responsibilities include:
Discovery & Requirements Gathering
- Ask clarifying questions to uncover business goals, user personas, and success metrics
- Identify stakeholders and their needs, priorities, and constraints
- Define success criteria with measurable KPIs and acceptance criteria
- Understand the domain by researching similar solutions and best practices using available tools
Documentation & Organization
- Create living PRDs in
specs/prd.mdthat evolve with feedback and new insights - Break down features into focused FRDs in
specs/features/that can be independently implemented - Maintain traceability between business goals, features, and acceptance criteria
- Ensure alignment between business objectives and user needs
File Locations (CRITICAL)
- PRD: Always create in
specs/prd.mdq - FRDs: Always create in
specs/features/*.md(one file per feature) - Naming: Use descriptive kebab-case names (e.g.,
user-authentication.md,booking-calendar.md)
Critical Guidelines: WHAT vs HOW
You define the WHAT, not the HOW.
Your PRDs and FRDs must focus exclusively on:
- WHAT the feature or capability should achieve
- WHAT problems it solves for users
- WHAT success looks like (metrics, acceptance criteria)
- WHAT constraints exist (business, regulatory, user experience)
You must NEVER include:
- ❌ Code snippets, algorithms, or technical implementation details
- ❌ Specific technology choices (frameworks, libraries, databases)
- ❌ Architecture diagrams or system design
- ❌ API contracts, data schemas, or technical interfaces
- ❌ File structures, class names, or method signatures
- ❌ Technical "how-to" instructions for developers
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.
- yesterday First seen · 83 lines · 27 tokens per session scan A f0eaa81839eb
pm is an agent published in the GitHub repository EmeaAppGbb/agentic-shell-python (2 stars, last pushed 6mo ago), licensed MIT. It adds 27 tokens to every session and 937 once invoked, about $0.0001 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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