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 Cristhianzl/claude-skills-czl --skill threat-modelinggit clone --depth 1 https://github.com/Cristhianzl/claude-skills-czlWrote 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/cristhianzl/claude-skills-czl/threat-modeling)<a href="https://agentmods.dev/skills/cristhianzl/claude-skills-czl/threat-modeling"><img src="https://agentmods.dev/badge/skills/cristhianzl/claude-skills-czl/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/cristhianzl/claude-skills-czl/threat-modeling"><img src="https://agentmods.dev/badge/skills/cristhianzl/claude-skills-czl/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 | $0.00158 | $0.02068 |
| Opus 5 | $0.00079 | $0.01034 |
| Sonnet 5 | $0.00032 | $0.00414 |
| Haiku 4.5 | $0.00016 | $0.00207 |
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 12d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling
Threat modeling is structured anticipation: you reason about how a system can be attacked while it is still cheap to change — at design time, on paper or in a diagram, before the code exists. The output is not a document; it is a set of mitigations wired to tests and a habit of asking "what could go wrong?" continuously.
This skill runs on Shostack's Four Question Framework (Adam Shostack, Threat Modeling: Designing for Security): What are we working on? What can go wrong? What are we going to do about it? Did we do a good job? Everything else — STRIDE, DFDs, risk ranking — serves those four questions.
Read first (always)
List learnings/ and read every file relevant to the current system (the domain, the trust boundaries, the third parties, the compliance regime). Project-specific assets, known attacker personas, accepted risks, and "in this system X is out of scope because Y" decisions live there and override the defaults in this SKILL.md. If a learning conflicts with this file, the learning wins — mention it to the user.
If learnings/ holds only its README, proceed with the defaults below.
Why this matters
Most vulnerabilities are design flaws, not coding bugs — a missing trust boundary, an unverified assumption, an authorization check that lives on the client. Code review and tests catch implementation defects; they rarely catch "we never decided who is allowed to do this." Threat modeling is the only activity that surfaces the flaw before the architecture sets. The Threat Modeling Manifesto frames it as a culture: a team that continuously finds and fixes, values a journey over a one-time artifact, and treats the model as living.
The Four Question Framework (the workflow)
1. What are we working on?
Define scope and assets, then draw the system.
- Assets: what is worth protecting? Data (PII, credentials, payment data, secrets), capabilities (admin actions, money movement), and reputation/availability. If nothing is worth stealing or breaking, you have no threat model.
- Diagram: build a Data Flow Diagram (DFD) — external entities, processes, data stores, data flows — and draw trust boundaries where privilege or control changes (network edge, process boundary, third-party call, user↔server). The boundaries are where the threats concentrate.
- Altitude: scope the system at the right zoom — one feature or service, not the whole company. Too big and you boil the ocean; too small and you miss the boundary crossing that matters.
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.
- 12d ago First seen · 90 lines · 158 tokens per session scan A 7bf968a5f236
threat-modeling is a skill published in the GitHub repository Cristhianzl/claude-skills-czl (5 stars, last pushed yesterday), licensed MIT. It adds 158 tokens to every session and 2,068 once invoked, about $0.0008 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 2026-08-31.
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