
oma-pm
Turn product requirements into scoped tasks with dependencies and acceptance criteria. Use for implementation planning and prioritization.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/gracefullight/stock-checker --skill oma-pm- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads oma-pm automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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.
Scenes
- PREPARE: Gather requirements, constraints, and context.
- REASON: Decompose work, identify dependencies, risks, and API/data contracts.
- ACT: Produce JSON plan and task-board-compatible output.
- VERIFY: Check task atomicity, acceptance criteria, security/testing coverage, and dependency shape.
- FINALIZE: Save plan artifacts and summarize execution path.
Transitions
- If requirements are ambiguous, clarify before decomposition.
- If tasks are tightly coupled, refine contracts or sequencing.
- If architecture is uncertain, coordinate with architecture before implementation planning.
- If the user needs automated execution, hand off to orchestrator after plan approval.
Failure and recovery
- If scope is too broad, split into phases.
- If acceptance criteria are vague, rewrite them into testable outcomes.
- If dependencies block parallel execution, surface sequencing explicitly.
Exit
- Success: plan is actionable, testable, prioritized, and compatible with orchestrator execution.
- Partial success: unresolved assumptions or dependencies are explicit.
Logical Operations
Actions
| Action | SSL primitive | Evidence |
|---|---|---|
| Read requirements/context | READ | User request and project context |
| Select planning structure | SELECT | Task template and workflow needs |
| Infer tasks and dependencies | INFER | Domain decomposition |
| Validate acceptance criteria | VALIDATE | Checklist and task schema |
| Write plan artifacts | WRITE | JSON plan and task-board markdown |
| Notify plan summary | NOTIFY | Final planning report |
Tools and instruments
- Task template, examples, ISO planning guide, shared API contracts
- Local filesystem for result artifacts
Canonical workflow path
1. Define API/data contracts.
2. Decompose tasks with agent, title, priority, dependencies, and acceptance criteria.
3. Save `.agents/results/plan-{sessionId}.json` using the injected session ID. Write the run-scoped report from the shared memory/result contract.
Resource scope
| Scope | Resource target |
|---|---|
MEMORY | Requirements, assumptions, dependencies |
LOCAL_FS | .agents/results/plan-{sessionId}.json, injected claim path and task/run-scoped report |
CODEBASE | Optional project context and API/data model references |
Preconditions
- Product goal and planning boundary are sufficiently clear.
- Required implementation domains can be identified.
Effects and side effects
- Creates plan artifacts and task boards.
- Influences downstream agent assignments and execution order.
- Does not directly implement code.
Guardrails
- For changed interfaces, reuse or define API/data contracts before dependent implementation tasks
- Every executable task has: agent, title,
{id, description}acceptance criteria, coveringrequired_checkswith exact argv/cwd, a replayabletaskprompt, priority tier (1 = independent, lower runs first), dependencies, and scope - Minimize dependencies for maximum parallel execution
- Security and testing are part of every task (not separate phases)
- Tasks should be completable by a single agent
- Output JSON plan + task-board.md for orchestrator compatibility
- When relevant, structure plans using ISO 21500 concepts, risk prioritization using ISO 31000 thinking, and responsibility/governance suggestions inspired by ISO 38500
Common Pitfalls
- Too Granular: "Implement user auth API" is one task, not five
- Vague Tasks: "Make it better" -> "Add loading states to all forms"
- Tight Coupling: tasks should use public APIs, not internal state
- Deferred Quality: testing is part of every task, not a final phase
References
-
Local code tools:
../_shared/core/code-intelligence.md(code search/navigation) -
Runtime identity and run-scoped reports:
../_shared/runtime/memory-protocol.md,../_shared/runtime/result-contract.md -
Execution steps (follow for the selected task):
resources/execution-protocol.md -
Plan examples:
resources/examples.md -
ISO planning guide:
resources/iso-planning.md -
Error recovery:
resources/error-playbook.md -
Task schema:
resources/task-template.json -
Ultrawork PLAN phase protocol:
resources/plan-phase-protocol.md(used when this skill runs inside the ultrawork workflow) -
Task board spec (orchestrator-consumed format):
../oma-orchestration/resources/memory-schema.md -
Human-readable tracker: when running inside the
/planworkflow, also generatedocs/plans/work/{NNN}-{name}.mdper.agents/workflows/plan.md -
API contract template (SSOT):
../_shared/core/api-contracts/template.md; write generated contracts to.agents/results/api-contracts/(run artifact) ordocs/plans/contracts/(durable spec) -
Context loading:
../_shared/core/context-loading.md -
Planning depth:
../_shared/core/difficulty-guide.md(unresolved scope or dependencies) -
Clarification:
../_shared/core/clarification-protocol.md -
Context budget:
../_shared/core/context-budget.md -
Lessons learned:
../_shared/core/lessons-learned.md(matching prior failure or requested retrospective)
FAQ
What does the oma-pm skill do?
Turn product requirements into scoped tasks with dependencies and acceptance criteria. Use for implementation planning and prioritization.
How do I install oma-pm?
Run npx skills add https://github.com/gracefullight/stock-checker --skill oma-pm in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/oma-pm/ (personal) or .claude/skills/oma-pm/ (project).
Which AI agents can use oma-pm?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is oma-pm safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains oma-pm?
It is published by gracefullight in gracefullight/stock-checker. It has 153 recorded installs.
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