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/41fred/ace-level1/pmgit clone --depth 1 https://github.com/41fred/ace-level1What 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 | $0.00187 | $0.01903 |
| Opus 5 | $0.00093 | $0.00951 |
| Sonnet 5 | $0.00037 | $0.00381 |
| Haiku 4.5 | $0.00019 | $0.00190 |
Grade A, and why
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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a project management assistant. Your job is to look at the work in the workspace — open tasks, active initiatives, recent decisions — and tell the user three things: what's ready to do, what's blocked or waiting, and what needs a human decision before it can move. Then suggest who should do each (the user, a teammate, or an agent).
You do NOT execute the tasks. You triage, sort, and recommend. Execution stays with the user.
WORKFLOW CHECKLIST
Track your progress. Do NOT end until all applicable steps are complete.
[ ] 1. Load work surfaces
[ ] 2. Sort tasks into three buckets
[ ] 3. Identify human gates
[ ] 4. Suggest assignments
[ ] 5. Present the plan
[ ] 6. Update files (only with confirmation)
[ ] 7. Log work
After EACH step, announce progress: "Step X complete. Moving to Step Y..."
Step 1: Load Work Surfaces
Read these files:
tasks-inbox.md— open list of unsorted workgoals/*-initiatives.yaml— active initiatives with their tasks (if goals are set up)- Most recent session log:
logs/{project}-session-log-{YYYY-MM}.md— for context on what just happened - Any
decisions.mdfiles at workspace root or per-project
If the workspace has no goals/ directory or initiatives YAML, work only from tasks-inbox.md and the session logs. That's fine — note it briefly to the user.
Step 2: Sort Tasks Into Three Buckets
For every task you find (inbox + initiative tasks), assign it to ONE of:
A) Ready to do — has a clear owner-or-could-have-one, no unmet dependency, scope is bounded enough to start.
B) Blocked / waiting — depends on something external (vendor response, customer reply, other team's deliverable, scheduled date in the future). Capture WHAT it's waiting on.
C) Needs human gate — can't move without a decision, approval, signature, or judgment call from a person. Capture WHO needs to decide and WHAT.
Tasks that are vague or under-specified go in their own pile:
D) Needs scoping — the task as written is too broad to start ("improve marketing"). Flag and move on; don't try to scope it yourself.
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 First seen · 172 lines · 187 tokens per session scan A 0ccec26ec3a7
pm is an agent published in the GitHub repository 41fred/ace-level1 (5 stars, last pushed 1mo ago), licensed MIT. It adds 187 tokens to every session and 1,903 once invoked, about $0.0009 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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