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 arozumenko/sdlc-skills --skill threat-modelinggit clone --depth 1 https://github.com/arozumenko/sdlc-skillsWrote 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/arozumenko/sdlc-skills/threat-modeling)<a href="https://agentmods.dev/skills/arozumenko/sdlc-skills/threat-modeling"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/threat-modeling/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/arozumenko/sdlc-skills/threat-modeling"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/threat-modeling.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 | $0.00051 | $0.01711 |
| Opus 5.5 | $0.00020 | $0.00684 |
| Sonnet 5.5 | $0.00010 | $0.00342 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
threat-modeling 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat modeling
You write a code-derived DFD and STRIDE threats with citations;
cite.mjs check <st>/threat-model.json re-reads every citation against the
bytes at head and validates the disposition grammar — everything else is
your judgement. Three rules hold everywhere:
- An element or a mitigation exists only because it is cited. Same
citation shape as a finding's (
references/dfd-elements.md), sameFAILED <locus>.<i> <why>vocabulary. - A mitigation is a claim, not a fact (
references/mitigations-as-claims.md) — you never grade your own claim; a freshsecurity-reviewer'smitigation-reviewdoes, and even that never rewrites the model. - You assign every element's, threat's and mitigation's own id
(
E-nnn/T-nnn/M-nnn) yourself; never writestate,oid,snippet_redactedorcheck_stamp—checkstamps those, and refuses a file carrying them from your hand (D10), the same rule as findings.idanywhere but element/threat/mitigation position is refused there too.
The shape
{ head?, elements: [{id, name, kind, citations}], threats: [{id, element_id, stride, title, mitigations, disposition}] }.
{
"elements": [
{ "id": "E-001", "name": "HTTP handler", "kind": "process",
"citations": [{ "path": "src/app.js", "lines": [1, 3], "snippet": "…" }] },
{ "id": "E-002", "name": "Orders table", "kind": "datastore",
"citations": [{ "path": "src/orders.js", "lines": [40, 45], "snippet": "…" }] }
],
"threats": [
{ "id": "T-001", "element_id": "E-002", "stride": "T",
"title": "Order total tampered before it is charged",
"mitigations": [
{ "id": "M-001", "claim": "createOrder recomputes the total from line items (lines 40-52)",
"citations": [{ "path": "src/orders.js", "lines": [40, 52], "snippet": "…" }] }
],
"disposition": "mitigated(M-001)" }
]
}
kind∈external | boundary | process | datastore | flow(references/dfd-elements.md— which letters apply to which kind is inreferences/stride.md).stride∈S | T | R | I | D | E, one letter per threat.disposition∈open | accepted(R-nnnn) | mitigated(M-nnn) | planned(TC-nnn) | out-of-scope(<reason>)— the full grammar, what each ref must name and the one-run sequence are inreferences/dispositions.md.ids (E-nnn,T-nnn,M-nnn) are unique across the whole model, not just within their array.
What ships with it
4 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 · 136 lines · 51 tokens per session scan A c5df8c512047
threat-modeling is a skill published in the GitHub repository arozumenko/sdlc-skills (25 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 1,711 once invoked, about $0.0002 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 2026-09-19.
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