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ariaxhanariaxhan/kernel-claude/skills/metrics/SKILL.md

metrics

Skill15 starsChanged 4 months agoMITView on GitHub

Observability dashboard. Session stats, agent tracking, hook performance, learning health. Triggers: metrics, stats, dashboard, observability.

20 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use docgen, scan and 7 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • prsolansSkill

    docgen

    Generate professional contract/agreement PDFs (and .docx CLM templates) from a declarative YAML config using the yaml-doc-generator tool ("docgen"). Use this whenever the user wants to create, manufacture, or mock up agreement documents — an MSA, NDA, SaaS/subscription agreement, amendment, exhibit, SOW, renewal notice, loan/credit agreement, fund/investment doc, BAA/DPA, government contract, or a whole document FAMILY between named parties — especially demo/test documents to load into Docusign Navigator/CLM or to feed an agreement-lifecycle agent. Triggers include "generate an MSA/NDA/agreement", "make demo contracts", "create a document family for <party> and <party>", "use docgen", or "use the yaml-doc-generator". Produces real PDFs with parties, clauses, and a manifest of critical dates (renewal/expiration).

    Also in 3 projects that use this

  • rajnavakotiSkill

    scan

    Run the AI dashboard scanner and generate the HTML report.

    Also in 3 projects that use this

  • OpenAISkill

    observability

    Vercel Observability expert guidance — Drains (logs, traces, speed insights, web analytics), Web Analytics, Speed Insights, runtime logs, custom events, OpenTelemetry integration, and monitoring dashboards. Use when instrumenting, debugging, or optimizing application performance and user experience on Vercel.

    Also in 3 projects that use this

  • BlockSkill

    plan

    Draft a TDD, PRD, or lightweight plan in the conversation without committing it.

    Also in 5 projects that use this

  • 0xSeroSkill

    security

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  • SentrySkill

    spec

    Produce a verified spec — problem, desired outcome, and acceptance criteria — before building. Use when given a GitHub/Linear issue link, when starting from a fuzzy in-conversation idea, or asked to "figure out what to do" / "scope this" / "what should I build" — whenever the *what* isn't yet pinned down. Grills the ambiguities, checks the premise against the code, and produces acceptance criteria you sign off on — then hands to design-first.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 14 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run agentdb metrics to get raw data

    line 20
  2. Distinctive:

    Use AskUserQuestion when: dashboard displayed and anomalies found Ask: "Anomaly in {metric}: {detail}.

    line 42
  3. Distinctive:

    Ask: "Anomaly in {metric}: {detail}.

    line 43

“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<skill id="metrics"><purpose> Surface actionable insights from KERNEL telemetry. Wraps `agentdb metrics` with analysis and recommendations. </purpose><execution> 1. Run `agentdb metrics` to get raw data 2. Analyze patterns and surface insights: - Session duration trends (are sessions getting longer? that may indicate complexity creep) - Agent success rates (are adversary verdicts calibrated?) - Hook failure rates (which guards need attention?) - Learning utilization (which learnings get reinforced vs ignored?) 3. Present dashboard with actionable recommendations

Example recommendations:

  • "64% tier 1 work — your skill set matches well"
  • "Adversary sample size < 5 — run /kernel:tearitapart more on tier 2+ work"
  • "detect-secrets had 2 failures — check patterns are current"
  • "3 learnings never reinforced in 30d — will be auto-pruned"</execution>

<on_start>

agentdb metrics
agentdb health

<ask_user> Use AskUserQuestion when: dashboard displayed and anomalies found Ask: "Anomaly in {metric}: {detail}. Want to investigate, or just note it?" Options: investigate, note and move on </ask_user> </on_start>

</skill>

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