Borrowing it
Nothing to install: this file belongs to MilindGaharwar/fettle. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MilindGaharwar/fettle/main/.opencode/commands/fettle-threat-model.mdgit 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/fettle-threat-model)<a href="https://agentmods.dev/commands/milindgaharwar/fettle/fettle-threat-model"><img src="https://agentmods.dev/badge/commands/milindgaharwar/fettle/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 5.1 | $0.00016 | $0.00239 |
| Opus 5 | $0.00008 | $0.00120 |
| Sonnet 5 | $0.00003 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
fettle-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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- threat-model — 89% identical, 9 lines differ
What it actually says
$ARGUMENTS refers to any text the user typed after the slash command.
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.
- 6d ago First seen · 30 lines · 16 tokens per session scan A 6e07c592eb1b
fettle-threat-model is a command published in the GitHub repository MilindGaharwar/fettle (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 16 tokens to every session and 239 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.
Other commands, from other repositories
scout-scan
Scan a path with Scout and walk through the security findings.
kb-ingest
Ingest external material into Sources/ inside the bound project KB, then update registry, index, and daily note as needed.
atomic-plan
Write a design doc (concepts, business rules, approaches) and a checkpoint-table spec (contract) for non-trivial work; inline spec only for trivial. Gauges triviality; loops spec authoring with subagents. Human-facing artifact, Mermaid diagrams allowed.
session-report
Capture what changed this session and why, scoped to the current branch. Read by ship verbs when synthesizing the commit message; deleted after a successful commit.
afo
Open feature worktree in terminal and start agent (shortcut for feature-open).
ai-review
AI code review of the staged git diff via the Claude API.