threat-model

A planning aid that describes a system's purpose, where it runs, and which inputs are trusted or untrusted before implementation.

In plain words
What is it for?
Use it when planning an API endpoint, data pipeline, agent loop, or other component that handles different sources of input.
Why use it?
It clarifies security boundaries early, so developers know what they are protecting and which inputs may be unsafe.

Skill for Claude CodeCodex

Part of the soundcheck plugin — 50 skills, 7 agents, 2 hooks shipped together

Install

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.

agentmods
npx agentmods add skills/thejefflarson/soundcheck/threat-model
Any agent
npx skills add thejefflarson/soundcheck --skill threat-model
Clone the repo
git clone --depth 1 https://github.com/thejefflarson/soundcheck

Made for: Claude Code, Codex.

Or install soundcheck, the plugin that ships this one along with the rest of its 50 skills, 7 agents, 2 hooks.

Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 759 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00078 $0.00759
Opus 5 $0.00039 $0.00380
Sonnet 5 $0.00016 $0.00152
Haiku 4.5 $0.00008 $0.00076

Measured 3d ago against content hash 529840e2a262, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

.claude/skills/threat-model/SKILL.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Threat Model (A06:2025)

What this checks

This skill produces the threat-model context a developer needs before writing the code: what is this thing, where will it run, what inputs do we trust, what inputs do we not. It does not emit findings or apply a checklist of "missing controls" — that's the developer's job once they have the context.

Single source of truth: this skill delegates to the threat-modeling subagent in .claude/agents/threat-modeling.md. The subagent's JSON output is the canonical threat-model shape.

Vulnerable patterns

This is an orchestrator skill. The agent it dispatches has no vulnerable-pattern catalog of its own — it produces context, and later auditors (vulnerability-audit, design-review, contract-audit) use that context to find code-level issues.

Procedure

Use the Agent tool to dispatch one threat-modeling subagent. Pass it the plan, spec, or codebase under discussion. The subagent returns a JSON object describing purpose, deployment, trusted inputs, and untrusted inputs.

Render that JSON as a Markdown report for the developer. Do not show the raw JSON. The report shape:

## Threat Model — <one-line summary derived from purpose>

**Purpose.** <purpose>

**Deployment.** <deployment>

**Trusted inputs** (the maintainer controls these; auditors should
not flag content originating here):

- <category 1>
- <category 2>
- ...

**Untrusted inputs** (cross a trust boundary; every one needs an
explicit handling step in the plan — validation, rate limit,
authentication, etc.):

- <category 1>
- <category 2>
- ...

---

*Use this as the design checklist for what your plan must address.
The skill produced context; deciding which controls to add is
yours.*

The closing line is intentional — this skill does not enforce specific controls or emit findings. It surfaces the trust-boundary picture; the developer decides what to add (auth on new endpoints, rate limits on user-facing surface, validation on external-service responses, …).

Read the full file on GitHub · 90 lines

Changes

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.

  1. 3d ago First seen · 90 lines · 78 tokens per session scan A 529840e2a262

Subscribe to this mod's changes

threat-model is a skill published in the GitHub repository thejefflarson/soundcheck (20 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 759 once invoked, about $0.0004 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 2026-08-30.

Related

Other skills, from other repositories

make-skill

Use this skill when sedimenting a session into a reusable workspace skill. Triggers when the user wants to turn the current conversation, workflow, or troubleshooting path into a SKILL.md. Phrases like 'turn this into a skill', 'remember how I did X', 'save this workflow', 'make a skill from this', and any /make-skill…

agentscope-ai/QwenPaw · 85 tokens

make-skill

用于把当前会话沉淀为可复用的 workspace skill。当用户希望把当前对话、工作流或排错路径写成 SKILL.md 时触发。触发表达包括「把这个变成 skill」「记住我是怎么做 X 的」「保存这个工作流」「make a skill from this」以及任何 /make-skill 调用。.

agentscope-ai/QwenPaw · 84 tokens

terraform-skill

Use when working with Terraform or OpenTofu - creating modules, writing tests (native test framework, Terratest), setting up CI/CD pipelines, reviewing configurations, choosing between testing approaches, debugging state issues, implementing security scanning (trivy, checkov), or making infrastructure-as-code…

agentscope-ai/QwenPaw · 62 tokens

docx

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when…

agentscope-ai/QwenPaw · 168 tokens

docx

当用户需要创建、读取、编辑或处理 Word 文档(.docx)时,使用此技能。触发场景包括提到“Word 文档”、“.docx”,或要求生成带目录、标题、页码、信头等格式的专业文档;也包括提取或重组 .docx 内容、插入或替换图片、在 Word 文件中查找替换、处理修订或批注,以及将内容整理为正式 Word 文档。如果用户要求生成“报告”“备忘录”“信函”“模板”等 Word / .docx 交付物,也应使用此技能。不要用于 PDF、电子表格、Google Docs,或与文档生成无关的一般编程任务。.

agentscope-ai/QwenPaw · 161 tokens

multi_agent_collaboration

Use this skill when another agent's expertise or context is needed, or when the user explicitly asks to involve another agent. First list agents, then use qwenpaw agents chat for two-way communication with replies.

agentscope-ai/QwenPaw · 47 tokens