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/lookup-sentinelWrote 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/lookup-sentinel)<a href="https://agentmods.dev/skills/liberty91ltd/cti-skills/lookup-sentinel"><img src="https://agentmods.dev/badge/skills/liberty91ltd/cti-skills/lookup-sentinel/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/lookup-sentinel"><img src="https://agentmods.dev/badge/skills/liberty91ltd/cti-skills/lookup-sentinel.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 | $0.00149 | $0.03067 |
| Opus 5 | $0.00075 | $0.01533 |
| Sonnet 5 | $0.00030 | $0.00613 |
| Haiku 4.5 | $0.00015 | $0.00307 |
Grade A, and why
lookup-sentinel 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lookup-sentinel
Query bridge to the organisation's own Microsoft Sentinel (Azure Log Analytics) workspace. Every other lookup in this pack asks the world about an indicator; this one asks your own telemetry: has this indicator been seen in our environment? Is this ATT&CK technique's behaviour present in our logs? It is scoping/exposure-checking, not enrichment — chain it after external lookups have told you what an indicator is, to establish whether it touched you.
Read-only. The CLI can only run queries and list schema — it cannot modify the workspace, close incidents, or create analytics rules.
The cardinal rule: discover before you query
No two Sentinel workspaces have the same tables. Table availability follows deployed connectors (Defender for Endpoint brings Device*, Entra ID brings SigninLogs, AMA/CEF brings CommonSecurityLog, …). A query referencing an absent table fails outright; worse, a hunt written for tables the environment doesn't ingest silently proves nothing.
So, in every session, before generating any hunt KQL:
- Run
tables(schema-known) and/oringestion(actually receiving data) once, and reuse the result for the rest of the session. probethe specific candidate tables for the hunt — schema-known tables can be empty.- Generate KQL only against tables the probe confirmed populated. When a preferred table is missing, walk the fallback ladder (below). When no suitable table exists, report the telemetry gap as a finding — do not fabricate a query, and do not quietly substitute a table that can't answer the question.
When to invoke
- An investigation skill (
/ip-investigationetc.) produced a malicious/suspicious verdict and you need the exposure answer: was it seen here? - The user asks to hunt for an ATT&CK technique, actor TTP set, or behaviour ("hunt for T1059 PowerShell abuse", "look for Kerberoasting")
- The user has IOCs (from a report, a feed,
/ioc-enrichment-workflow) and wants them swept across the environment - The user asks what telemetry/tables the Sentinel workspace has, or whether a planned detection would even have data
- The user asks to run or adapt a KQL query against live logs
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 · 160 lines · 149 tokens per session scan A bdf22ce1e0af
lookup-sentinel is a skill published in the GitHub repository Liberty91LTD/cti-skills (18 stars, last pushed 1mo ago), licensed MIT. It adds 149 tokens to every session and 3,067 once invoked, about $0.0007 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
ai-ad-copy-compliance-review
A risk-review assistant for advertising and sales copy. It examines provided material for possible concerns and suggests actions.
ai-agent-browser
A business-diagnosis assistant for marketing, operations, product, and sales questions. It breaks down a goal and produces a summary, findings, action suggestions, and reusable deliverables.
ai-article
A Chinese-language assistant for turning source material into article and content-operation deliverables. It is aimed at creators, marketers, technical teams, and media publishers.
ai-brand-voice-review
A business-diagnosis assistant for marketing, operations, services, and sales questions.
ai-browser-use
A business-diagnosis assistant for marketing, operations, product, and sales questions about how to approach a task.
ai-content-material-audit
A Chinese-language copy-review assistant for creators, marketers, operators, and media teams.