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 ctmgit 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/ctm)<a href="https://agentmods.dev/skills/izar/tm_skills/ctm"><img src="https://agentmods.dev/badge/skills/izar/tm_skills/ctm.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 | $0.00023 | $0.00392 |
| Opus 5 | $0.00012 | $0.00196 |
| Sonnet 5 | $0.00005 | $0.00078 |
| Haiku 4.5 | $0.00002 | $0.00039 |
Grade A, and why
ctm 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 6d 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.
What it actually says
Overview
Given a business case, a user-story, a development request or similar, examine it in the context of the project and the existing baseline threat model and decide if it is a "security notable event" according to Continuous Threat Modeling.
Method
Copy this checklist and track your progress:
Security notable event checklist
- [ ] Find a baseline threat model
- [ ] Enrich the request
- [ ] Use the CTM Developer Checklist
**Step 1: Find a baseline threat model
Examine the project's directory for documentation that resembles a threat model. If one is found, use that as the baseline threat model. If one is not found, ask the user if they would like to use the pytm skill to create one, or if they can provide a baseline threat model. Give the user the option to not have a baseline threat model but point out the quality of the analysis will be diminished.
**Step 2: Enrich the request
If a baseline threat model is available, use it to enrich the corpus of the request. Feel free to ask the user as many elucidative questions about the request as you consider necessary. Use the answers to enrich the request.
**Step 3: Use the CTM Developer Checklist
Using the content of ./Secure_Developer_Checklist.md try to identify in the user request instances that match the "If you did THIS ..." side of the reference table. If matches are found, use the "... then do THAT" respective field to suggest mitigations to the issue identified.
There can be many matches in any given request. Return all those matches.
If there are notable events, suggest to the user that a ticket be created reflecting this change so the threat model can be updated.
What ships with it
1 file 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.
- 6d ago First seen · 41 lines · 23 tokens per session scan A 94019a9347fe
ctm is a skill published in the GitHub repository izar/tm_skills (19 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 392 once invoked, about $0.0001 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.
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