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 ulises-jeremias/agent-toolkit --skill threat-modelinggit clone --depth 1 https://github.com/ulises-jeremias/agent-toolkitWrote 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/ulises-jeremias/agent-toolkit/threat-modeling)<a href="https://agentmods.dev/skills/ulises-jeremias/agent-toolkit/threat-modeling"><img src="https://agentmods.dev/badge/skills/ulises-jeremias/agent-toolkit/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/ulises-jeremias/agent-toolkit/threat-modeling"><img src="https://agentmods.dev/badge/skills/ulises-jeremias/agent-toolkit/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 | $0.00048 | $0.02031 |
| Opus 5.5 | $0.00019 | $0.00812 |
| Sonnet 5.5 | $0.00010 | $0.00406 |
| Haiku 4.5 | $0.00005 | $0.00203 |
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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling — STRIDE + Agentic Threats
Guide architecture → threat model → security review → security acceptance criteria. Produces a STRIDE table augmented with agentic-specific threats (prompt injection, tool poisoning, excessive agency, inter-agent trust), risk-ranked with mitigations and acceptance criteria.
Evidence-linked, portable, incremental. Architecture discovery reuses C4/Mermaid inputs (#369); outputs feed agentic-security-reviewer + owasp-agentic-review + security-reviewer.
Sources: Microsoft STRIDE (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege) + OWASP Threat Modeling + OWASP Agentic Security (prompt injection, tool poisoning, excessive agency, data leakage, insecure plugin/MCP). See https://learn.microsoft.com/en-us/azure/security/develop/threat-modeling-tool-threats and https://owasp.org/www-project-threat-model/ .
When to use
- New system/C4 design (
architectoutput), new data flow (user → agent → tool → external), new trust boundary (skill composition, MCP addition, swarm handoff) - Before
security-reviewer/owasp-agentic-reviewprioritizes mitigations - On architecture change — incremental mode re-runs only on deltas
Inputs
| Input | Source | Required |
|---|---|---|
| Architecture diagram | architect / C4/Mermaid (#369) — docs/architecture/*.md, Mermaid C4Context/flowchart |
Yes (or textual description for small scopes) |
| Assets | Code + docs: skills, agents, MCP registry, secrets, data stores | Yes |
| Trust boundaries | User ↔ agent, agent ↔ MCP, agent ↔ external host, inter-agent, skill composition | Yes |
| Data flows | audit-capability.py shell/network/MCP/hooks surface, registry YAML, hook configs |
Yes |
| Actors | Users, agents (by persona), MCP servers, external services | Yes |
Outputs
threat-model.mdperreferences/threat-model-template.md: assets/boundaries/flows/actors → STRIDE + agentic threats table (severity, likelihood, impact, confidence, evidence) → mitigations → security acceptance criteria- Incremental diff when
architecture discoverychanged - Handoff:
agentic-security-reviewerconsumes findings for OWASP review;security-reviewerfor app-layer vulns
What ships with it
1 file 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 · 101 lines · 48 tokens per session scan A 9c87fa52c71a
threat-modeling is a skill published in the GitHub repository ulises-jeremias/agent-toolkit (19 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 2,031 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 2026-09-04.
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