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 timwukp/agent-skills-best-practice --skill threat-modelinggit clone --depth 1 https://github.com/timwukp/agent-skills-best-practiceWrote 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/timwukp/agent-skills-best-practice/threat-modeling)<a href="https://agentmods.dev/skills/timwukp/agent-skills-best-practice/threat-modeling"><img src="https://agentmods.dev/badge/skills/timwukp/agent-skills-best-practice/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/timwukp/agent-skills-best-practice/threat-modeling"><img src="https://agentmods.dev/badge/skills/timwukp/agent-skills-best-practice/threat-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00084 | $0.01038 |
| Opus 5 | $0.00042 | $0.00519 |
| Sonnet 5 | $0.00017 | $0.00208 |
| Haiku 4.5 | $0.00008 | $0.00104 |
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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling (STRIDE)
Produce a lightweight, sprint-compatible threat model: 15-30 minutes of structured analysis, not a multi-week security assessment. The output is a threat model document plus security stories the team can schedule.
Process
- Establish the data flow. Ask for (or derive from the code/design) the feature's data flow: actors, entry points, services, data stores, and trust boundaries. Summarize it as
Actor → Component → ... → Store, marking each trust boundary crossing with||. If the user has architecture docs or code, read them instead of asking. - Walk the STRIDE categories against each trust boundary crossing (see table below). For each plausible threat, capture: description, category, likelihood (H/M/L), impact (H/M/L), and a concrete mitigation. Skip categories that genuinely don't apply — do not pad the table.
- Rate risk as High if likelihood or impact is High and the other is at least Medium; Low only if both are Low; otherwise Medium.
- Generate security stories for every High and Medium threat using the story format below (or hand off to the security-story-writing skill if it is available). Low threats go to the residual risk list with a one-line acceptance rationale.
- Deliver the document using the template, and tell the user which stories should enter the next sprint.
STRIDE Categories
| Category | Question to ask | Typical mitigations |
|---|---|---|
| Spoofing | Can someone pretend to be a user, service, or device? | Strong authentication, mTLS, signed tokens |
| Tampering | Can data be modified in transit or at rest? | TLS, integrity checks, signed payloads, immutable logs |
| Repudiation | Can an actor deny performing an action? | Audit logging with identity + timestamp, log integrity |
| Information disclosure | Can data leak to the wrong party? | Encryption, least-privilege access, output filtering, masking |
| Denial of service | Can the component be made unavailable? | Rate limiting, quotas, timeouts, autoscaling, circuit breakers |
| Elevation of privilege | Can a user gain rights they shouldn't have? | AuthZ checks at every boundary, input validation, sandboxing |
What ships with it
2 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 · 77 lines · 84 tokens per session scan A cf9fb5e24761
threat-modeling is a skill published in the GitHub repository timwukp/agent-skills-best-practice (10 stars, last pushed 2d ago), licensed MIT. It adds 84 tokens to every session and 1,038 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 2026-08-31.
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