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 skills/jayrha/agentskills/threat-modelernpx skills add JayRHa/AgentSkills --skill threat-modelergit clone --depth 1 https://github.com/JayRHa/AgentSkillsWrote 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/jayrha/agentskills/threat-modeler)<a href="https://agentmods.dev/skills/jayrha/agentskills/threat-modeler"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/threat-modeler.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 | $0.00132 | $0.02312 |
| Opus 5 | $0.00066 | $0.01156 |
| Sonnet 5 | $0.00026 | $0.00462 |
| Haiku 4.5 | $0.00013 | $0.00231 |
Grade A, and why
threat-modeler 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 yesterday.
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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeler (STRIDE)
Overview
Keywords: STRIDE, threat model, threat modeling, data flow diagram, DFD, trust boundary, attack surface, spoofing, tampering, repudiation, information disclosure, denial of service, elevation of privilege, DREAD, risk rating, mitigation, countermeasure, security review, attacker, asset.
This skill drives a rigorous, repeatable threat-modeling session using the STRIDE methodology popularized by Microsoft's Security Development Lifecycle. It turns an architecture description into:
- A data flow diagram (DFD) with trust boundaries.
- A per-element threat enumeration mapped to the six STRIDE categories.
- A prioritized mitigation plan with risk ratings and concrete countermeasures.
The output is a single threat model document. Threat modeling answers four questions (the Shostack frame): What are we building? What can go wrong? What are we going to do about it? Did we do a good enough job?
Bundled resources:
references/stride-catalog.md— STRIDE definitions, the element-to-threat applicability matrix, attacker archetypes, and a large catalog of concrete threats and standard mitigations per category.references/risk-rating.md— DREAD and Likelihood×Impact rating rubrics with scoring tables and prioritization guidance.scripts/threat_report.py— stdlib-only Python tool that ingests a YAML/JSON threat list and emits a sorted Markdown risk register plus summary stats.templates/threat-model.md— the fill-in document the skill produces.examples/url-shortener.md— a complete worked example (input architecture → DFD → threats → mitigations).
Workflow
Follow these steps in order. Do not skip decomposition — most missed threats come from a sloppy DFD.
1. Scope and gather context
Establish what is in and out of scope. Capture:
- Assets: what an attacker wants (credentials, PII, money, availability, integrity of records).
- System purpose and the primary user journeys.
- Tech stack, deployment model, and external dependencies (third-party APIs, SaaS, queues, databases).
- Existing controls already in place (auth, TLS, WAF, RBAC).
What ships with it
5 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.
- yesterday First seen · 129 lines · 132 tokens per session scan A 378cdffdbf43
threat-modeler is a skill published in the GitHub repository JayRHa/AgentSkills (4 stars, last pushed 1mo ago), licensed MIT. It adds 132 tokens to every session and 2,312 once invoked, about $0.0007 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 2026-09-03.
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