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 skills add byerlikaya/claude-starter-kit --skill threat-modelgit clone --depth 1 https://github.com/byerlikaya/claude-starter-kitWrote 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/byerlikaya/claude-starter-kit/threat-model)<a href="https://agentmods.dev/skills/byerlikaya/claude-starter-kit/threat-model"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/threat-model/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/byerlikaya/claude-starter-kit/threat-model"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/threat-model.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00065 | $0.00876 |
| Opus 5.5 | $0.00026 | $0.00350 |
| Sonnet 5.5 | $0.00013 | $0.00175 |
| Haiku 4.5 | $0.00006 | $0.00088 |
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 1mo 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model
Trigger phrases: "threat model", "attack surface", "scope the audit", "trust boundary"
Scope first, scan second. A security scan with no map produces noise; a threat model tells the scanner (and
security-scan) where to look and what matters — the single biggest lever on false positives.
The one idea to keep — the litmus test: if patching one line of code makes an entry disappear, it was a vulnerability, not a threat. Threats survive patching (they name what an attacker wants and the surface they arrive through); a vulnerability is only evidence that raises a threat's likelihood.
Kit adaptation (local, .claude/):
security-expert-cskruns this to scope beforesecurity-scan. Outputdocs/THREAT_MODEL.mdis internal (§4.3). Stack-agnostic. §4 Prohibitions apply.
When
- Before a first
security-scanof a system, or when scan output is noisy / unscoped. - After a significant new surface — a new API, a new integration, a new trust boundary.
Two modes
- interview — the owner is available: ask the four questions below, one at a time.
- bootstrap — no owner: derive the model from code + past advisories, then flag what only the owner can confirm.
Method — the four questions (Shostack), one at a time
Never dump a questionnaire; ask, capture into the schema, move on. Mirror the user's language.
- What are we building? system context, assets worth protecting, entry points and trust boundaries.
- What can go wrong? open-ended first; then, per entry point, fall back to STRIDE; derive 5-8 domain-specific attack classes at the right granularity — "IDOR on dataset rows", "integer overflow on length fields" — not "web vulnerabilities".
- What are we doing about it? impact · residual likelihood · status · controls per threat; "accept the
risk, with a written reason" (
risk_accepted) is a valid answer. - Did we do a good job? read the ranked table back; coverage-check that every entry point appears.
What ships with it
2 files 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.
- 1mo ago First seen · 60 lines · 65 tokens per session scan A f310edd814c8
threat-model is a skill published in the GitHub repository byerlikaya/claude-starter-kit (24 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 876 once invoked, about $0.0003 per session on Opus 5.5. 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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