agentleFS
OpenAIKnown publisheropenai/community-plugins/plugins/grafana-observability/skills/inspect-infrastructure-health/SKILL.md

inspect-infrastructure-health

Skill18 starsChanged 2 months agoApache-2.0View on GitHub

Inspect reviewed Grafana infrastructure evidence for host or fleet CPU usage, memory load, disk space, and system load. Use for server-health checks, capacity symptoms, resource saturation, disk pressure, cloud or local host comparisons, and bounded infrastructure triage.

The file

We split this skill into the rules it gives an agent

11 rules. About 0 are common, 3 are distinctive, and 8 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 8

    Very specific

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

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

    Run the fixed grafana.infrastructure pack and present its normalized evidence without modifying the monitored environment.

    line 8
  2. Very specific:

    Use only grafana_profile_status, grafana_list_packs, grafana_run_pack, grafana_get_evidence, and grafana_resolve_link.

    line 12
  3. Distinctive:

    Never accept or construct PromQL, SQL, URLs, headers, datasource IDs, panel JSON, variables, or raw provider requests.

    line 14
  4. Distinctive:

    Never write to Grafana, a datasource, a host, an alert, or a deployment.

    line 15
  5. Very specific:

    Call grafana_profile_status({profileAlias}).

    line 21
  6. Very specific:

    Call grafana_list_packs({profileAlias}) and require the exact active pack ID grafana.infrastructure.

    line 22
  7. Distinctive:

    Create one non-secret idempotency key for this attempt and reuse it for any exact retry.

    line 23
  8. Very specific:

    Call grafana_run_pack with that key, the aliases, packId: "grafana.infrastructure", origin, current window, and optional baseline window.

    line 24
  9. Very specific:

    Call grafana_get_evidence({reportRef,evidenceRef}) only for evidence references returned by this report and needed to support a material …

    line 26
  10. Very specific:

    Call grafana_resolve_link({reportRef,linkRef}) only for a link reference returned by the same report when a trusted Grafana panel link …

    line 27
  11. Very specific:

    Treat an issue as a rule-backed alert only when it has classification: SIGNED_RULE and kind: ALERT.

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

Inspect Infrastructure Health

Run the fixed grafana.infrastructure pack and present its normalized evidence without modifying the monitored environment.

Safety contract

  • Use only grafana_profile_status, grafana_list_packs, grafana_run_pack, grafana_get_evidence, and grafana_resolve_link.
  • Accept only profile and scope aliases; one declared LIVE, REPLAY, or SIMULATED origin; bounded current and baseline windows; and opaque references returned by these tools.
  • Never accept or construct PromQL, SQL, URLs, headers, datasource IDs, panel JSON, variables, or raw provider requests.
  • Never write to Grafana, a datasource, a host, an alert, or a deployment. This skill cannot authorize remediation or a patch.
  • Confirm the environment before using LIVE. Do not silently switch among LIVE, REPLAY, and SIMULATED.

Workflow

  1. Establish profileAlias, scopeAlias, origin, and a current window no longer than seven days. Ask for an earlier equal-duration, non-overlapping baseline only when comparison matters.
  2. Call grafana_profile_status({profileAlias}). Stop on ERROR or blocked readiness; disclose PARTIAL readiness before continuing.
  3. Call grafana_list_packs({profileAlias}) and require the exact active pack ID grafana.infrastructure.
  4. Create one non-secret idempotency key for this attempt and reuse it for any exact retry.
  5. Call grafana_run_pack with that key, the aliases, packId: "grafana.infrastructure", origin, current window, and optional baseline window.
  6. Inspect CPU usage, memory load, disk free space, and system load in the returned signal order. Preserve returned units, severity, and direction; do not combine unlike units.
  7. Call grafana_get_evidence({reportRef,evidenceRef}) only for evidence references returned by this report and needed to support a material claim.
  8. Call grafana_resolve_link({reportRef,linkRef}) only for a link reference returned by the same report when a trusted Grafana panel link helps the user verify the evidence. Never accept a URL as input.

Treat an issue as a rule-backed alert only when it has classification: SIGNED_RULE and kind: ALERT. Treat classification: DEVIATION as a deviation, not an anomaly. Do not infer root cause from saturation alone, and do not treat absent or stale telemetry as a healthy host.

Interpret report status exactly

  • COMPLETE: all expected evidence completed; evaluate each signal and issue rather than saying “healthy” by default.
  • EMPTY: the bounded scope and window returned no usable evidence; this is an evidence gap, not zero usage.
  • STALE: the evidence is too old for a current health claim; report its observed and collected times.
  • PARTIAL: expected evidence is missing, failed, or mixed; state which conclusions remain unsupported.
  • CONTRADICTORY: evidence conflicts; show the conflicting evidence references and do not choose a preferred value.
  • ERROR: collection failed or was rejected; report the sanitized error and stop.

Completion format

Return scope, origin, current and baseline windows, overall status, a compact CPU/memory/disk/load table, issues with their returned classification, evidence gaps or contradictions, evidence references for every material claim, and trusted panel links only when resolved from report-owned references.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.