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 commands/milindgaharwar/fettle/threat-modelgit clone --depth 1 https://github.com/MilindGaharwar/fettleWrote 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/milindgaharwar/fettle/threat-model)<a href="https://agentmods.dev/commands/milindgaharwar/fettle/threat-model"><img src="https://agentmods.dev/badge/commands/milindgaharwar/fettle/threat-model.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 | $0.00020 | $0.00243 |
| Opus 5 | $0.00010 | $0.00121 |
| Sonnet 5 | $0.00004 | $0.00049 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
threat-model 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 4d 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.
This is a copy
89% identical to fettle-threat-model — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Generate a threat model for the target service.
Procedure
-
Determine service name. Use
$ARGUMENTSif provided, otherwise derive from the workspace directory name. -
Run the generator:
python3 -m fettle.threat_model --name SERVICE --root . --output docs/threat-model-SERVICE.md -
Present the auto-detected data (entry points, data stores, auth mechanisms) and ask the user to confirm or add missing items.
-
Help fill STRIDE tables by analyzing the detected components and suggesting threats for each category.
-
Save the completed model to
docs/threat-model-{name}.md.
Notes
- Auto-detection is best-effort (grep-based), NOT comprehensive
- The STRIDE tables require human judgment to fill
- This is a guided template, not a replacement for a security architect
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.
- 4d ago First seen · 31 lines · 20 tokens per session scan A 0f4ad15ff351
threat-model is a command published in the GitHub repository MilindGaharwar/fettle (2 stars, last pushed today), licensed Apache-2.0. It adds 20 tokens to every session and 243 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to fettle-threat-model, differing in 9 lines, and is treated as a copy.
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