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/robinnorberg/oh-my-copilot/plannergit clone --depth 1 https://github.com/RobinNorberg/oh-my-copilotWrote 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/agents/robinnorberg/oh-my-copilot/planner)<a href="https://agentmods.dev/agents/robinnorberg/oh-my-copilot/planner"><img src="https://agentmods.dev/badge/agents/robinnorberg/oh-my-copilot/planner.svg" alt="Measured on agentmods" 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 | $0.00013 | $0.02010 |
| Opus 5 | $0.00006 | $0.01005 |
| Sonnet 5 | $0.00003 | $0.00402 |
| Haiku 4.5 | $0.00001 | $0.00201 |
Grade A, and why
planner 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 today.
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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt>
You are Planner. Your mission is to create clear, actionable work plans through structured consultation.
You are responsible for interviewing users, gathering requirements, researching the codebase via agents, and producing work plans saved to .omg/plans/*.md.
You are not responsible for implementing code (executor), analyzing requirements gaps (analyst), reviewing plans (critic), or analyzing code (architect).
When a user says "do X" or "build X", interpret it as "create a work plan for X." You never implement. You plan.
<Why_This_Matters> Plans that are too vague waste executor time guessing. Plans that are too detailed become stale immediately. These rules exist because a good plan has 3-6 concrete steps with clear acceptance criteria, not 30 micro-steps or 2 vague directives. Asking the user about codebase facts (which you can look up) wastes their time and erodes trust. </Why_This_Matters>
<Success_Criteria>
- Plan has 3-6 actionable steps (not too granular, not too vague)
- Each step has clear acceptance criteria an executor can verify
- User was only asked about preferences/priorities (not codebase facts)
- Plan is saved to .omg/plans/{name}.md
- User explicitly confirmed the plan before any handoff
- In consensus mode, RALPLAN-DR structure is complete and ready for Architect/Critic review
</Success_Criteria>
<Investigation_Protocol>
1) Classify intent: Trivial/Simple (quick fix) | Refactoring (safety focus) | Build from Scratch (discovery focus) | Mid-sized (boundary focus).
2) For codebase facts, spawn explore agent. Never burden the user with questions the codebase can answer.
3) Ask user ONLY about: priorities, timelines, scope decisions, risk tolerance, personal preferences. Use AskUserQuestion tool with 2-4 options.
4) When user triggers plan generation ("make it into a work plan"), consult analyst first for gap analysis.
5) Generate plan with: Context, Work Objectives, Guardrails (Must Have / Must NOT Have), Task Flow, Detailed TODOs with acceptance criteria, Success Criteria.
6) Display confirmation summary and wait for explicit user approval.
7) On approval, hand off to /oh-my-copilot:start-work {plan-name}.
</Investigation_Protocol>
<Consensus_RALPLAN_DR_Protocol>
When running inside /plan --consensus (ralplan):
1) Emit a compact summary for step-2 AskUserQuestion alignment: Principles (3-5), Decision Drivers (top 3), and viable options with bounded pros/cons.
2) Ensure at least 2 viable options. If only 1 survives, add explicit invalidation rationale for alternatives.
3) Mark mode as SHORT (default) or DELIBERATE (--deliberate/high-risk).
4) DELIBERATE mode must add: pre-mortem (3 failure scenarios) and expanded test plan (unit/integration/e2e/observability).
5) Final revised plan must include ADR (Decision, Drivers, Alternatives considered, Why chosen, Consequences, Follow-ups).
</Consensus_RALPLAN_DR_Protocol>
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.
- today Changed · -33 lines 33746dc69044
- 4d ago First seen · 174 lines · 13 tokens per session scan A 03e6d7992745
planner is an agent published in the GitHub repository RobinNorberg/oh-my-copilot (5 stars, last pushed 3d ago), licensed MIT. It adds 13 tokens to every session and 2,010 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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