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 izar/tm_skills --skill tmntgit clone --depth 1 https://github.com/izar/tm_skillsWrote 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/izar/tm_skills/tmnt)<a href="https://agentmods.dev/skills/izar/tm_skills/tmnt"><img src="https://agentmods.dev/badge/skills/izar/tm_skills/tmnt.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 5.1 | $0.00034 | $0.00525 |
| Opus 5 | $0.00017 | $0.00262 |
| Sonnet 5 | $0.00007 | $0.00105 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
tmnt - Threat Model New Things 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 7d 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Given a named technology, library, approach, architecture design, package, programming concept or similar, examine it in the context of the project and the existing baseline threat model and expose its significance from a threat modeling point of view.
Method
Ask the user as many clarifying questions as necessary at any step of your process. To being, copy this checklist and track your progress:
Threat Modeling New Things
- [ ] Identify the new technology in question.
- [ ] Consider its basic characteristics.
- [ ] Offer a brief overview, no more than 20 lines.
- [ ] Examine its security implications, if any.
**Step 1: Identify the new thing in question.
If you cannot easily identify the intent of the user in what they named as the focus of their research, ask as many clarifying questions as needed. Perform web searches and offer possible short descriptions of what you find, until you are clear and certain that you have indeed identified what the user is interested in.
**Step 2: Consider its basic characteristics.
At this step, do not perform a deep dive into the subject at hand. Instead, consider its basic characteristics, how it might be or not a security notable issue by itself and in terms of the project the user is working on, if that is known. There is no output to the user at this step, but keep your consideration handy for use.
**Step 3: Offer a brief overview, no more than 20 lines.
Offer the user a brief overview of the subject as you have understood it, no more than 20 lines. Note what the use of the subject is, and if you know which project the user is working on, how the subject might apply, or not, to it. After that, offer options, if any, that are newer or known to be more secure.
**Step 4: Examine its security implications, if any.
Now perform a deeper dive into the subject and offer a list of security issues it may resolve or may bring into the context of whatever the user is working on. If you know what is being worked on, offer observations in that context, otherwise, offer generic security-related items that the subject requested may surface. If appropriate, offer a 3-questions summary: what are we building, what could go wrong, and what can be done about it.
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.
- 7d ago First seen · 41 lines · 34 tokens per session scan A c81a7456247b
tmnt - Threat Model New Things is a skill published in the GitHub repository izar/tm_skills (19 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 525 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…