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/commands/mshadmanrahman/pm-pilot/plan)<a href="https://agentmods.dev/commands/mshadmanrahman/pm-pilot/plan"><img src="https://agentmods.dev/badge/commands/mshadmanrahman/pm-pilot/plan/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/commands/mshadmanrahman/pm-pilot/plan"><img src="https://agentmods.dev/badge/commands/mshadmanrahman/pm-pilot/plan.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 | $0.00019 | $0.00101 |
| Opus 5.5 | $0.00008 | $0.00040 |
| Sonnet 5.5 | $0.00004 | $0.00020 |
| Haiku 4.5 | $0.00002 | $0.00010 |
Grade A, and why
plan 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
/plan
Create an implementation plan before coding.
Usage
/plan {feature or task description}
Behavior
- Invoke the planner agent from
agents/planner.md - Restate requirements, identify risks, create phased plan
- Present plan and WAIT for user approval
- Do not write code until plan is confirmed
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 · 19 lines · 19 tokens per session scan A 0ef2faec3a2c
plan is a command published in the GitHub repository mshadmanrahman/pm-pilot (22 stars, last pushed 17d ago), licensed MIT. It adds 19 tokens to every session and 101 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 commands, from other repositories
skene-init
Initialize Skene configuration for this project. Creates .skene.config (TOML), sets up provider and API key (or SKENEAPIKEY), and runs validation.
skene-status
Check implementation status from skene-context/engine.yaml. Validates features, action vs code-only mode, and that trigger/function SQL exists in migrations; detail shows latest matching file and (+N) if duplicates.
lessons
Lists the feedback memories captured for the current project (and globally) — the "lessons" learned from user corrections.
qa-loop
Autonomous loop AUDIT (parallel) → VALIDATE → FIX → VERIFY → CHECK with stopping criteria.
skene-analyze
Analyze current codebase for PLG opportunities. Scans tech stack, detects existing growth features, identifies revenue leakage, and updates the feature registry.
skene-build
Build an implementation prompt for the selected growth loop. Generates context-aware instructions with code examples and testing checklists.