df-observability
Skill4 starsChanged 2 months agoApache-2.0View on GitHub
Dark Factory Observability stage: make the consumable surface (dashboards and queryable traces keyed to scenarios, verified rendering live data) a named deliverable — a /metrics endpoint nobody can see is not observability. Triggers on "observability", "dashboards", "Grafana", "correlationId trace", "telemetry surface".
In this repository43 other files it gives its agents.
- skills/vercel-react-best-practices/AGENTS.mdAGENTS.md
- agent-notepadSkill
- architecture-reviewerSkill
- backend-service-auditorSkill
- channel-listenerSkill
- code-reviewerSkill
- coder-file-transferSkill
- cold-start-generatorSkill
- creating-skillsSkill
- critical-thinkingSkill
- dark-factory-buildSkill
- dependency-risk-auditorSkill
- df-adversary-gateSkill
- df-app-walkthroughSkill
- df-context-storeSkill
- df-data-transform-lensSkill
- df-dispatch-subagentsSkill
- df-infrastructureSkill
- df-product-ownerSkill
- df-qaSkill
- df-solution-architectSkill
- df-tdd-developerSkill
- df-ui-verifySkill
- df-video-intakeSkill
- dx-maintainability-reviewerSkill
- frontend-auditorSkill
- handoffSkill
- microservices-architectSkill
- production-readiness-reviewerSkill
- repo-docsSkill
- requirements-discoverySkill
- sc-auditSkill
- sc-devSkill
- scope-initSkill
- scope-retireSkill
- security-threat-modelerSkill
- service-mapperSkill
- test-quality-gatekeeperSkill
- vercel-react-best-practicesSkill
- vinculum-loopSkill
- vinculum-mapSkill
- web-design-guidelinesSkill
- work-autonomouslySkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 11
Rule of thumb: if an agent cannot answer *"did scenario TS-0x run, and where did it succeed or fail?"* by looking at a dashboard or running …
≈ “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.
Files
Dark Factory — Observability Standard (the agents' eyes)
Overview
Observability is the sensory apparatus the agents use to build, deploy, and test — not optional garnish. Emitting telemetry is necessary but not sufficient: a :9090/metrics endpoint nobody can see is not observability. This standard makes the consumable surface a named, verified deliverable.
Rule of thumb: if an agent cannot answer "did scenario TS-0x run, and where did it succeed or fail?" by looking at a dashboard or running one query, the system is not observable yet — no matter how many metrics it emits.
The three legs — Emit → Surface → Act
| Leg | Question | Owner | Artifact |
| Emit | Is telemetry produced? | Developer (service anatomy) | :9090/metrics, JSON logs w/ correlationId, :8080/healthz, DLQ depth |
| Surface | Can a human/agent see and query it? | SA designs · Infra builds · QA verifies | dashboards + queryable log/trace views that render live data (the historically missing leg) |
| Act | Does it fire before customers notice? | SA names · Infra wires | alerts → a sink |
Emission is platform default (deltas only). Surface is product-specific and must be delivered + verified — that is the gap this standard closes.
Required baseline dashboard set (the floor)
Flow/saga (end-to-end path of each PO scenario) · Throughput · Tiered failure log filtered by the log level field ("level":"ERROR"), not a substring (?i)error (substring matching floods false positives from name collisions) · Correlation/trace lookup (a $correlationId variable pulling every log + span across services) · DLQ + queue depth · Latency (p50/p95/p99) · System health. Panels keyed to PO scenarios.
The acceptance bar — "verified rendering live data"
A dashboard that POSTs valid JSON but shows "No data" is not delivered. Every view reachable at a known URL; every panel renders live data (against the datasource, not just schema-valid); $correlationId returns real cross-service results; every alert rule evaluates. Verification is by observation, not assertion.
Anti-patterns
- Emit-only —
/metricsexists, no dashboard renders it → QA can't capture evidence. - Schema-valid, no data — dashboard JSON loads but every panel shows "No data".
- Substring failure filters —
(?i)errorinstead of the level field. - Hand-clicked dashboards — not in version control as code → lost on cluster rebuild.
- Human-only access — reachable by a human in prod, but the QA/Dev agent has no programmatic path in dev/test.
Does it work?
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Your trail
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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.

