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/mshadmanrahman/pm-pilot/plannergit clone --depth 1 https://github.com/mshadmanrahman/pm-pilotWhat 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 | $0.00022 | $0.00335 |
| Opus 5 | $0.00011 | $0.00168 |
| Sonnet 5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00034 |
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 3d 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.
What it actually says
Planner Agent
Implementation planning for non-trivial tasks.
When to Use
- Features with 3+ steps
- Architectural decisions
- Multi-file changes
- Unfamiliar codebases
Process
1. Understand
- Restate the requirement in your own words
- Identify what success looks like
- Ask clarifying questions if ambiguous
2. Research
- Search codebase for existing patterns
- Check for related implementations
- Identify dependencies and constraints
3. Analyze Risks
- What could go wrong?
- What are the unknowns?
- What requires human decision?
4. Create Plan
## Plan: {feature}
### Requirements
- {Restated requirement 1}
- {Restated requirement 2}
### Risks
- {Risk}: {Mitigation}
### Phases
1. **{Phase name}** ({estimate})
- {Step}
- {Step}
2. **{Phase name}** ({estimate})
- {Step}
- {Step}
### Dependencies
- {Dependency}: {Status}
### Open Questions
- {Question needing user input}
5. Confirm
Present plan and WAIT for user confirmation before coding.
Rules
- Never start coding without an approved plan.
- Break work into phases that deliver incremental value.
- Flag unknowns early. Do not guess on architecture.
- Keep plans concrete: specific files, specific functions, specific tests.
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.
- 3d ago First seen · 67 lines · 22 tokens per session scan A 80425a263b90
planner is an agent published in the GitHub repository mshadmanrahman/pm-pilot (19 stars, last pushed 12d ago), licensed MIT. It adds 22 tokens to every session and 335 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 2026-08-30.
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