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 williamzujkowski/standards --skill threat-modelinggit clone --depth 1 https://github.com/williamzujkowski/standardsWrote 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/williamzujkowski/standards/threat-modeling)<a href="https://agentmods.dev/skills/williamzujkowski/standards/threat-modeling"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/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/williamzujkowski/standards/threat-modeling"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/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 | $0.00043 | $0.02292 |
| Opus 5.5 | $0.00017 | $0.00917 |
| Sonnet 5.5 | $0.00009 | $0.00458 |
| Haiku 4.5 | $0.00004 | $0.00229 |
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 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.
This is a copy
80% identical to graphql-api-design — 562 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling
Identify, prioritize, and mitigate security threats systematically using STRIDE methodology
Level 1: Quick Reference
STRIDE Threat Categories
threats:
S_spoofing:
description: Impersonating something or someone else
targets: [authentication, identity]
example: "Using stolen credentials to access system"
T_tampering:
description: Modifying data or code maliciously
targets: [data_integrity, code_integrity]
example: "Altering transaction amounts in transit"
R_repudiation:
description: Claiming to not have performed an action
targets: [logging, audit_trails]
example: "Denying fraudulent transaction was performed"
I_information_disclosure:
description: Exposing information to unauthorized parties
targets: [confidentiality, data_protection]
example: "Leaking customer PII through error messages"
D_denial_of_service:
description: Making system unavailable or degraded
targets: [availability, performance]
example: "Overwhelming API with requests"
E_elevation_of_privilege:
description: Gaining unauthorized higher access level
targets: [authorization, access_control]
example: "Exploiting bug to gain admin rights"
Four Key Questions
-
What are we building?
- System architecture, components, data flows
- Trust boundaries, entry/exit points
-
What can go wrong?
- Apply STRIDE to each component
- Identify threat scenarios
-
What should we do about it?
- Prioritize threats (DREAD scoring)
- Design mitigations
-
Did we do a good job?
- Review threat model coverage
- Validate mitigations
Essential Checklist
Planning Phase:
- Identify system scope and boundaries
- Document assets and data flows
- Define security objectives
- Assemble threat modeling team
Analysis Phase:
- Create data flow diagrams (DFD)
- Mark trust boundaries
- Apply STRIDE to each element
- Document threat scenarios
- Build attack trees
What ships with it
12 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.
- example-threats.yaml 7.0 KB
- README.md 6.2 KB
- REFERENCE.md 25 KB
- resources/README.md 2.6 KB
- resources/stride-examples.md 13 KB
- scripts/README.md 2.9 KB
- scripts/threat-report-generator.py 14 KB runs code
- templates/data-flow-diagram.md 13 KB
- templates/mitigation-plan.md 10 KB
- templates/README.md 1.8 KB
- templates/stride-template.md 5.8 KB
- templates/threat-scenario.md 9.3 KB
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 · 411 lines · 43 tokens per session scan A ab9b963f3966
threat-modeling is a skill published in the GitHub repository williamzujkowski/standards (18 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 2,292 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 80% identical to graphql-api-design, differing in 562 lines, and is treated as a copy.
Other skills, from other repositories
performing-threat-modeling-with-owasp-threat-dragon
Use OWASP Threat Dragon to create data flow diagrams, identify threats using STRIDE and LINDDUN methodologies, and generate threat model reports for secure design review.
pytm
Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and automated security threat identification. Use when: (1) Creating threat models programmatically using Python code, (2) Generating data flow diagrams (DFDs) with automatic STRIDE threat identification…
pytm
Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and automated security threat identification. Use when: (1) Creating threat models programmatically using Python code, (2) Generating data flow diagrams (DFDs) with automatic STRIDE threat identification…
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code-confidence-map
Assesses code comprehensibility and maintainability risk. Use when the user asks about code confidence, risk, maintainability, tech debt, code health, or whether code is safe to change. Also use when the user asks to analyze code quality, scan for risks, check if code is messy or complex, audit code, do a code…
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