Instrumented service scaffold
Skill selamy-labs/agent-skills/skills/instrumented-service-scaffold
Use when creating or reviewing a new long-running service so observability, runtime flags, tests, coverage gates, and release controls exist from the first commit.From its SKILL.md
npx -y skills add selamy-labs/agent-skills --skill instrumented-service-scaffoldAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Instrumented Service Scaffold
Use this workflow when authoring or reviewing a new service, worker, daemon, API, or other long-running software component.
Baseline
From the first commit, the service must include:
- OpenTelemetry traces, metrics, and structured logs wired through a real exporter.
- A runtime flag client (e.g. OpenFeature) backed by a flag source that can be reviewed and rolled back without a redeploy.
- A formatter, linter, and type/static-analysis gate using the language's standard tools.
- Complexity and nesting budgets that stop new outliers before they turn into review-time style debates.
- A test harness: unit tests, contract tests where interfaces matter, at least one feature check for promised behavior, and a coverage gate sized to the service's risk.
- PR-only delivery with branch protection and required checks for tests, coverage, release policy, and build/deploy validation.
- State-changing delivery workflows (deploy, apply, image-publish) that
serialize per target via a concurrency group with
cancel-in-progress: false; read-only CI may cancel superseded runs. - Conventional release or changelog metadata when the repo uses automated versioning.
- For state where change history matters (quotas, balances, membership,
config), record changes as replayable events rather than only the latest
value; compose with
event-sourcing(https://github.com/selamy-labs/agent-skills/tree/main/skills/event-sourcing).
Do not defer these to a later hardening pass. If the service is too small to justify them, document that decision and keep it short-lived or non-production.
Self-Debug Loop
The owner of the service needs the ability to:
- Observe its own traces, metrics, and structured logs.
- Form a concrete hypothesis from that telemetry.
- Change behavior through a reviewed runtime flag or a normal PR.
- Verify the user/system artifact and the telemetry after the change.
The loop is incomplete if it depends on a human manually spelunking logs on the owner's behalf.
Conformance Check
Before claiming the service is ready, grep the real repository for each item — not the intent, the artifact:
- OpenTelemetry init code and at least one meaningful span or metric on a business-critical flow.
- Runtime flag client init pointing at a reviewed flag source.
- Formatter, linter, static-analysis, complexity, and coverage config enforced by CI (the config files plus the CI job that runs them).
- At least one feature-level behavior check for the primary promise, not only line coverage.
- State-changing workflows (deploy, apply, release, image-publish) that declare queue-not-cancel concurrency scoped to serialize each target environment, state file, or published artifact.
- Required PR checks and release-policy checks present in the repo settings or IaC source of truth.
- For any state the service declared history-bearing: an append-only event/change record plus the code path that emits it — not only a latest-value column or gauge.
- Docs that explain how to observe the service and change a flag.
Record any gap as a blocker or an explicit temporary waiver with a removal date. Do not call the service production-ready while the baseline is missing.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.