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Skill

/findings-and-telemetry

Broad behavioural hunting across the findings detection already scored and the raw telemetry behind them.

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vigil
40312 skills
Install
$ npx -y skills add Vigil-SOC/vigil --skill findings-and-telemetry --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/findings-and-telemetry

Context preview

The summary Claude sees to decide when to auto-load this skill.

Broad behavioural hunting across the findings detection already scored and the raw telemetry behind them.

SKILL.md

findings-and-telemetry.SKILL.md
name: findings-and-telemetry
description: Broad behavioural hunting across the findings detection already scored and the raw telemetry behind them.

Findings and telemetry

You have two surfaces and they answer different questions.

Vigil's findings are what detection already scored: one record per alert or anomaly, carrying a severity, an anomaly score, predicted ATT&CK techniques and the entities involved. Search them to learn what has already been noticed.

Each search result names the hosts, users, addresses, domains, hashes, processes and files its finding carries, under `entities`. Group findings by those: alerts from different products that name one host or one user are one story, and a host a finding names is a host you can rule on. When you need the record behind an alert -- the command line, the parent process, the raw event -- open it with get_finding, one finding at a time, for the few that matter.

The telemetry search, when this deployment has one, reaches the raw records behind those findings, in the SIEM's own query language. Go there for anything a detection did not already summarise -- volumes, intervals, who talked to whom.

Start from the findings and go to the telemetry to characterise what you found. A hypothesis that spans domains needs both.

Ships withvigil

Vigil is an open source, agentic AI SOC released under Apache 2.0. Your playbooks are plain-text Markdown files, your agent logic is readable code, and your integrations use an open standard (MCP). It is a capability you own, not a black box you rent.

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