Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Liberty91LTD/cti-skillsnpx agentmods add skills/liberty91ltd/cti-skills/control-coverage-mappingWrote 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/liberty91ltd/cti-skills/control-coverage-mapping)<a href="https://agentmods.dev/skills/liberty91ltd/cti-skills/control-coverage-mapping"><img src="https://agentmods.dev/badge/skills/liberty91ltd/cti-skills/control-coverage-mapping/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/liberty91ltd/cti-skills/control-coverage-mapping"><img src="https://agentmods.dev/badge/skills/liberty91ltd/cti-skills/control-coverage-mapping.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 | $0.00118 | $0.03979 |
| Opus 5.5 | $0.00047 | $0.01592 |
| Sonnet 5.5 | $0.00024 | $0.00796 |
| Haiku 4.5 | $0.00012 | $0.00398 |
Grade A, and why
control-coverage-mapping 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.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Control Coverage Mapping
Answers one question with evidence instead of opinion: which attacker techniques does this control set actually address, and at what strength?
The usual way to answer it is to put people in a room and negotiate a percentage. This skill replaces that with a join against a public, versioned table that both sides can read and challenge. Where the evidence rates a control's strength, that rating is carried through unchanged. Where it does not, the output says so rather than inventing a number.
When to invoke
- The user asks what their controls cover, where the gaps are, or how to prioritise security spend
- The user asks what controls they should have for a given threat, campaign or sector, with no baseline in hand
- A threat profile has produced a technique list and the next question is "so are we covered?"
- A FAIR or risk-quantification workflow needs the Resistance Strength input
- Board or audit reporting needs a defensible coverage statement with citations
- A vendor claims a product "stops" a technique and you want the public evidence
- A detection team asks what telemetry to collect for a given threat (
--telemetry)
Do NOT invoke for: deciding whether a control is correctly configured in a specific environment (that is a testing question, not a mapping question), or for producing a single vulnerability percentage (see Limits).
Four modes
Be clear which question you are answering, because the inputs and the honest wording differ.
| Question | Mode | Needs a baseline? |
|---|---|---|
| "What does my current control set cover?" | --controls baseline.csv |
yes |
| "What controls should I have for this threat?" | omit --controls |
no |
| "What do I actually implement?" | --mitigations |
no |
| "What do I collect and correlate?" | --telemetry |
no |
# COVERAGE — gap assessment against what they actually run
python3 tools/clis/map_controls.py --controls baseline.csv --techniques techs.json
# RECOMMEND — no baseline needed
python3 tools/clis/map_controls.py --techniques T1566,T1190,T1078 --top 15
# ACTIONABLE — ATT&CK mitigations and telemetry, combinable
python3 tools/clis/map_controls.py --techniques techs.json --mitigations --telemetry
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.
- 3d ago Changed · -39 tokens per session d91e4fb77980
- 2mo ago First seen · 202 lines · 157 tokens per session scan A abf5dcfd45a8
control-coverage-mapping is a skill published in the GitHub repository Liberty91LTD/cti-skills (36 stars, last pushed 4d ago), licensed MIT. It adds 118 tokens to every session and 3,979 once invoked, about $0.0005 per session on Opus 5.5. 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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