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.
git clone --depth 1 https://github.com/mshadmanrahman/pm-pilotWrote 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/mshadmanrahman/pm-pilot/planner)<a href="https://agentmods.dev/agents/mshadmanrahman/pm-pilot/planner"><img src="https://agentmods.dev/badge/agents/mshadmanrahman/pm-pilot/planner/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/agents/mshadmanrahman/pm-pilot/planner"><img src="https://agentmods.dev/badge/agents/mshadmanrahman/pm-pilot/planner.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 | $0.00022 | $0.00335 |
| Opus 5.5 | $0.00009 | $0.00134 |
| Sonnet 5.5 | $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 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.
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.
- 1mo ago First seen · 67 lines · 22 tokens per session scan A 80425a263b90
planner is an agent published in the GitHub repository mshadmanrahman/pm-pilot (22 stars, last pushed 23d ago), licensed MIT. It adds 22 tokens to every session and 335 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
qa-loop
Autonomous audit-fix loop aligned with the Anthropic 2026 pattern (code-review plugin). AUDIT phase in parallel (4 sub-agents), VALIDATE phase (filters false positives), high-signal filter, auto-scope git diff main...HEAD. Flags --audit-only and --comment for read-only and inline PR post modes.
wcag-audit
Accessibility audit based on WCAG 2.1/2.2. Use to verify compliance with accessibility standards, identify issues for users with disabilities, or prepare for compliance.
qa-claudemd
Audit of compliance with the project's CLAUDE.md and repo conventions. Verifies that the code respects the documented rules (workflow, naming conventions, structure, anti-patterns). Use as a sub-agent in qa-loop for the Anthropic 2026 pattern.
ops-infra-code
Infrastructure as Code (Terraform, OpenTofu). Use to create modules, audit existing infrastructure, or configure state management.
qa-audit
Complete project quality audit. Combines OWASP security, GDPR, WCAG accessibility and performance. Use for a global audit before going to production.
data-pipeline
ETL/ELT pipeline design. Use to create data flows, transformations, and orchestration.