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 skills/joris887/exosuit/optimizenpx skills add joris887/exosuit --skill optimizegit clone --depth 1 https://github.com/joris887/exosuitWhat 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 | $0.00027 | $0.02250 |
| Opus 5 | $0.00014 | $0.01125 |
| Sonnet 5 | $0.00005 | $0.00450 |
| Haiku 4.5 | $0.00003 | $0.00225 |
Grade A, and why
optimize 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
optimize
Optimizing: $ARGUMENTS
Argument Parsing
| Argument | Required | Default | Description |
|---|---|---|---|
<goal> |
Yes | - | What to optimize (e.g., "increase test coverage", "reduce bundle size") |
--metric "<command>" |
Yes | - | Shell command that outputs the metric value. Pipe through grep if needed to isolate the number |
--target <N> |
Yes | - | Target value to reach |
--direction min|max |
No | max |
Whether to minimize or maximize the metric |
--max <N> |
No | 20 | Maximum experiments before stopping |
Examples:
/optimize "increase test coverage" --metric "npm test -- --coverage 2>&1 | grep 'All files' | awk '{print $10}'" --target 90 --direction max
/optimize "reduce bundle size" --metric "npm run build 2>&1 | grep 'gzipped' | awk '{print $3}'" --target 150 --direction min --max 30
/optimize "eliminate lint warnings" --metric "npm run lint 2>&1 | tail -1 | grep -oE '[0-9]+ problems'" --target 0 --direction min
Failure State Persistence
At loop entry, write docs/sessions/.failure-state.md:
---
status: active
skill: optimize
phase: "baseline"
phase_name: "Baseline Measurement"
started_at: "[ISO-8601 timestamp]"
story: "[goal from $ARGUMENTS]"
branch: "[from git branch --show-current]"
next_action: "Measure baseline metric"
files_modified: []
---
## Context
Goal: [goal]
Metric command: [command]
Target: [target] (direction: [min|max])
Max experiments: [max]
Current experiment: 0
Best value: [pending]
Update at each experiment iteration. Delete when optimization completes or max experiments reached.
Process
1. Pre-Flight
Run verify-clean-git-state micro-component. Confirm:
- Working tree is clean (no uncommitted changes)
- On a feature branch (not main/master)
- Git is available
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 270 lines · 27 tokens per session scan A 6c899b8654b7
optimize is a skill published in the GitHub repository joris887/exosuit (4 stars, last pushed 13d ago), licensed MIT. It adds 27 tokens to every session and 2,250 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 2026-08-31.
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