agentleFS
selamy-labsselamy-labs/agent-skills/skills/live-state-verification/SKILL.md

live-state-verification

Skill0 starsChanged 6 days agoMITView on GitHub

Use when verifying service health, deployed state, cluster objects, credentials, or automation results where the wrong auth context can produce false empty results.

The file

We split this skill into the rules it gives an agent

11 rules. About 0 are common, 10 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈10

    Distinctive · estimate

    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. Distinctive:

    Use this when a result depends on the real system state, not just logs or a local assumption.

    line 8
  2. Distinctive:

    Use the correct identity and environment for the artifact being checked.

    line 13
  3. Distinctive:

    Do not suppress stderr on presence or health checks.

    line 14
  4. Distinctive:

    Prefer direct artifact checks over proxy logs.

    line 17
  5. Distinctive:

    Run the primary check without hiding errors.

    line 29
  6. Distinctive:

    Run a second check from a different plane:

    line 30
  7. Distinctive:

    do not store credentials or sensitive payloads

    line 38
  8. Distinctive:

    When the artifact is an agent tool, MCP server, sidecar, or gateway, startup success is not enough.

    line 42
  9. Very specific:

    Check inherited runtime environment, especially HOME, cache, config, and durable data directories after privilege drops.

    line 46
  10. Distinctive:

    Check required persisted files are owned and readable/writable by the runtime UID, not just by root during entrypoint setup.

    line 48
  11. Distinctive:

    Prefer an exact-image or deployed-pod probe over a host/root smoke when HOME, UID, or filesystem ownership can differ.

    line 54

≈ “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

Live State Verification

Use this when a result depends on the real system state, not just logs or a local assumption.

Verification Rules

  • Use the correct identity and environment for the artifact being checked.
  • Do not suppress stderr on presence or health checks; auth errors and empty results can look identical after redirection.
  • Corroborate important claims from at least two views.
  • Prefer direct artifact checks over proxy logs.

Procedure

  1. Name the artifact:
    • deployed revision, job run, pod, service endpoint, repository setting, secret version, document, email, or workflow result.
  2. Confirm the auth context:
    • account/user
    • cluster/project/region
    • kubeconfig or exec plugin
    • token scope or installation
  3. Run the primary check without hiding errors.
  4. Run a second check from a different plane:
    • API plus UI/CLI
    • controller status plus workload behavior
    • repository metadata plus branch protection behavior
    • pod environment plus application-level operation
    • startup logs plus the exact model-facing tool or endpoint call
  5. Preserve concise evidence:
    • command class, artifact id, timestamp, observed status
    • do not store credentials or sensitive payloads

Runtime Tool Verification

When the artifact is an agent tool, MCP server, sidecar, or gateway, startup success is not enough. Verify the operation from the same environment that the model or runtime child process uses.

  • Check inherited runtime environment, especially HOME, cache, config, and durable data directories after privilege drops.
  • Check required persisted files are owned and readable/writable by the runtime UID, not just by root during entrypoint setup.
  • Probe a required model-facing operation, such as a harmless list/accounts or health/list-tools call, after rollout.
  • Report the actual failing stage separately from package/image/access failures so CI does not misclassify runtime setup errors.
  • Prefer an exact-image or deployed-pod probe over a host/root smoke when HOME, UID, or filesystem ownership can differ.

Failure Modes

  • Missing exec credential plugin on PATH.
  • Checking the wrong cluster or project.
  • Token has read access to one repo/org but not the target.
  • Stderr redirection hides a permission error.
  • A controller is healthy while the workload it manages is not.
  • A log says "sent" or "applied" but the external artifact never changed.
  • A root-run startup canary passes while the runtime child keeps HOME=/root or cannot read persisted files after dropping privileges.
  • A gateway registers tools but a required model-facing tool call still fails.

Done

  • The claim is backed by the real artifact or two independent views.
  • Runtime/tool claims include a same-UID or model-facing operation, not only a root-run startup smoke.
  • Any uncertainty is stated as uncertainty rather than upgraded to "verified."

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Your trail

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