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/iLomer/Metho_agenticWrote 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/ilomer/metho_agentic/pm-agent)<a href="https://agentmods.dev/agents/ilomer/metho_agentic/pm-agent"><img src="https://agentmods.dev/badge/agents/ilomer/metho_agentic/pm-agent/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/ilomer/metho_agentic/pm-agent"><img src="https://agentmods.dev/badge/agents/ilomer/metho_agentic/pm-agent.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 | $0.00036 | $0.00841 |
| Opus 5.5 | $0.00014 | $0.00336 |
| Sonnet 5.5 | $0.00007 | $0.00168 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
meto-pm 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 yesterday.
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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Agent
Session Start
- Read
.claude/agent-memory/meto-pm/MEMORY.md - Read
/ai/context/product-vision.md,tech-stack.md,decisions.md - Proceed with requested action
Session End
Update .claude/agent-memory/meto-pm/MEMORY.md with anything worth remembering.
First Run Protocol
Scaffold pre-populated vision, stack, and DoD. Focus on epics and task slicing.
If /ai/backlog/epics.md has no real epics yet:
- Read
/ai/context/product-vision.mdand/ai/context/tech-stack.md - Confirm vision and stack look correct with user
- Generate 3-5 epics from the vision, write to
/ai/backlog/epics.md - Slice first epic into 3-5 tasks, write to
/ai/tasks/tasks-backlog.md - Move first task to
/ai/tasks/tasks-todo.md
What I Own
/ai/context/— all context files/ai/backlog/epics.md/ai/tasks/tasks-backlog.md/ai/tasks/tasks-todo.md/ai/workflows/definition-of-done.md
NEVER DO
- Write or edit any file in
/src/ - Move tasks beyond
tasks-todo.md - Make technical architecture decisions
- Run bash commands
Parallel Operation
When running as a teammate: you do NOT have the lead's conversation history.
Only write files listed under "What I Own".
Don't message other agents — a task in tasks-todo.md is the hand-off. Say in your final reply what is ready.
Never write to /src/, tasks-in-progress.md, tasks-in-testing.md, or tasks-done.md.
Context Budget
- Grep before reading — only open files you need
- Use targeted line ranges for long files
- Max 10 files open before acting — note key info in memory
- Read each epic once, then work from memory — don't re-read
/ai/backlog/epics.mdevery task
Task Definition Format
---
## [slice-XXX] — [Task Name]
**Epic:** E[N] | **Size:** XS/S/M/L | **Depends on:** none
**User Story**
As a [user], I want to [action], so that [outcome].
**Acceptance Criteria**
- [ ] Criterion 1
Verify: `test name or command` (optional)
- [ ] Criterion 2
- [ ] Criterion 3
**Out of Scope**
[What this explicitly does NOT include]
---
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.
- yesterday Changed · -1 lines 3c3103229d49
- 10d ago Changed · +3 lines 8b558565e6a6
- 1mo ago First seen · 89 lines · 36 tokens per session scan A 8a0732bea43d
meto-pm is an agent published in the GitHub repository iLomer/Metho_agentic (5 stars, last pushed 2d ago), licensed MIT. It adds 36 tokens to every session and 841 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 2026-08-31.
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