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/2389-research/simmer/simmer-setupnpx skills add 2389-research/simmer --skill simmer-setupgit clone --depth 1 https://github.com/2389-research/simmerWrote 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/skills/2389-research/simmer/simmer-setup)<a href="https://agentmods.dev/skills/2389-research/simmer/simmer-setup"><img src="https://agentmods.dev/badge/skills/2389-research/simmer/simmer-setup.svg" alt="Measured on agentmods" 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 | $0.00076 | $0.03964 |
| Opus 5 | $0.00038 | $0.01982 |
| Sonnet 5 | $0.00015 | $0.00793 |
| Haiku 4.5 | $0.00008 | $0.00396 |
Grade A, and why
simmer-setup 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 5d 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 — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simmer Setup
Inspect the artifact, infer what "better" means and how to measure it, propose an assessment to the user, produce the setup brief that drives the entire refinement loop.
Core principle: Inspect first, infer second, propose third, confirm last. The agent does the thinking — the user validates, adjusts, or overrides. Never ask the user to describe something the agent can read.
Phase 1: Identify and Inspect
Identify the Artifact
Look for:
- A file path mentioned or open in context
- Text pasted by the user
- A directory path or workspace
- A description of something to generate from scratch (seedless mode)
If ambiguous, ask once:
What are we refining?
1. A file (give me the path)
2. Something you'll paste
3. A workspace/directory (give me the path)
4. Generate from a description (I'll create the starting point)
Set mode and artifact type:
| Mode | Artifact Type | When |
|---|---|---|
| from-file | single-file | User provides a file path |
| from-paste | single-file | User pastes content |
| from-workspace | workspace | User provides a directory path |
| seedless | single-file or workspace | User describes what to create |
Inspect the Artifact
For single-file (from-file or from-paste):
- Read the file/content
- Identify what kind of artifact it is (prose, code, prompt, config, etc.)
- Note any evaluator references (test commands, benchmark scripts mentioned in comments)
- Note any output format expectations visible in the content
For workspace (from-workspace):
- List the directory contents
- Read key files: config files, entry points, scripts, READMEs
- Look specifically for:
- Evaluator scripts: files named
evaluate.*,test.*,benchmark.*, or scripts referenced in configs/READMEs - Validation scripts: files named
validate.*,check.*, or quick-test variants - Config files:
config.json,config.yaml,.env, etc. — these reveal what parameters can be varied - Output examples: any sample output, expected output, or ground truth files
- Strategy/plugin dirs: directories like
strategies/,plugins/,models/that indicate extensibility points - Prompt files:
prompt.md,system.txt, template files — things the generator can modify
- Evaluator scripts: files named
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.
- 5d ago First seen · 399 lines · 76 tokens per session scan A d7390538054c
simmer-setup is a skill published in the GitHub repository 2389-research/simmer (14 stars, last pushed 2mo ago), licensed MIT. It adds 76 tokens to every session and 3,964 once invoked, about $0.0004 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 2026-08-30.
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