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 skills add gracefullight/docusaurus-plugins --skill oma-pmgit clone --depth 1 https://github.com/gracefullight/docusaurus-pluginsWrote 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/skills/gracefullight/docusaurus-plugins/oma-pm)<a href="https://agentmods.dev/skills/gracefullight/docusaurus-plugins/oma-pm"><img src="https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-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.
<a href="https://agentmods.dev/skills/gracefullight/docusaurus-plugins/oma-pm"><img src="https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-pm.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 | $0.00055 | $0.01505 |
| Opus 5.5 | $0.00022 | $0.00602 |
| Sonnet 5.5 | $0.00011 | $0.00301 |
| Haiku 4.5 | $0.00006 | $0.00151 |
Grade A, and why
oma-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.
This is a copy
91% identical to oma-pm — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Agent - Product Manager
Scheduling
Goal
Turn ambiguous or complex product requests into actionable, dependency-aware plans with clear tasks, priorities, acceptance criteria, API contracts, and risk/governance notes.
Intent signature
- User asks for planning, requirements, specification, scope, prioritization, task breakdown, roadmap, or implementation plan.
- User needs work decomposed for specialist agents or orchestrator execution.
When to use
- Breaking down complex feature requests into tasks
- Determining technical feasibility and architecture
- Prioritizing work and planning sprints
- Defining API contracts and data models
When NOT to use
- Implementing actual code -> delegate to specialized agents
- Performing code reviews -> use QA Agent
Expected inputs
- User request, product goal, constraints, target users, and acceptance expectations
- Existing codebase context, architecture constraints, and integration points
- Optional standards, risk, governance, or orchestration requirements
Expected outputs
- JSON plan and
task-board.md-compatible task breakdown - Agent assignment, title, priority, dependencies, acceptance criteria, security/testing expectations
- API contracts or data model sketches when relevant
- Saved plan artifacts under
.agents/results/
outputs:
- name: plan
description: PM task breakdown JSON for orchestrator consumption
artifact: ".agents/results/plan-*.json"
required: true
Dependencies
resources/execution-protocol.md, examples, task template, and ISO planning guide- Shared API contract references and project context-loading rules
- Downstream specialist skills for implementation
Control-flow features
- Branches by ambiguity, dependency structure, risk level, and whether standards/governance framing is needed
- Produces planning artifacts rather than code
- Optimizes for parallelizable specialist-agent execution
Structural Flow
Entry
- Clarify the product goal, constraints, and target deliverables.
- Identify technical domains and required contracts.
- Decide whether ISO/risk/governance framing is relevant.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 158 lines · 55 tokens per session scan A b14c96cba563
oma-pm is a skill published in the GitHub repository gracefullight/docusaurus-plugins (23 stars, last pushed 27d ago), licensed MIT. It adds 55 tokens to every session and 1,505 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to oma-pm, differing in 29 lines, and is treated as a copy.
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