Support

Skill lantisprime/claude-sdlc/skills/support

A governance layer for AI-assisted software delivery. Plan, scope, approve, build, test, release — with human sign-off at every gate.

Install

npx -y skills add lantisprime/claude-sdlc --skill support

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use this skill during Phase 7 after a successful deployment to generate or update monitoring, logging, alerting, and observability artifacts that catch exceptions and issues in the deployed code. Produces platform-neutral scripts when no observability platform is configured, and integrates with Grafana/Datadog/CloudWatch via MCP when configured. Trigger after deploy, or when the user says "add monitoring", "observability", "alerts", "dashboards", or "what should we watch for?".

SKILL.md

3.1 KB, as published. Nobody here has run it

Support (Phase 7)

Make the change observable in production.

Prerequisite

.claude/sdlc/gates/deploy-<task-slug>.md must exist and be signed.

Step 1 — Identify what to watch

From the plan's in-scope surface and the security/NFR sections of the architecture, enumerate:

New code paths → structured log events at key decision points
New endpoints or RPCs → request count, error rate, latency (p50/p95/p99)
New background jobs → run count, duration, failure rate
New external calls → timeout, failure, retry counters
New failure modes from the threat model → alerts

For each, write: what to measure, why, threshold for alert, who is paged, runbook link.

Step 2 — Produce artifacts

Write to .claude/sdlc/monitoring/<task-slug>/:

Logging changes — code deltas (in a follow-up PR, not this build's PR) or config changes
Metrics — platform-appropriate config (Prometheus rules, Datadog monitors, CloudWatch alarms)
Dashboards — JSON or TOML for the configured platform; a README if none is configured
Alerts — with routing (oncall rotation / channel), severity, auto-resolve conditions
Runbook stub — runbook.md with symptom → diagnostic → mitigation

Step 3 — Integrate (when configured)

If an observability platform is configured in .claude/sdlc/env.json:

Grafana/Datadog via MCP → propose dashboard and alert changes as pull requests or API calls; never auto-apply production alert changes without human confirmation
CloudWatch → propose IaC changes

Never silently mutate production monitoring.

Step 4 — Validate

Generate a synthetic failure in a non-production environment and confirm the alert fires.
Confirm the runbook entry matches what an on-call engineer would need at 3am.

Human gate

Summarize: what's now being watched, what's alerted, runbook status. Sign-off → .claude/sdlc/gates/support-<task-slug>.md.

What this skill must NOT do

Do not auto-apply changes to production alerting.
Do not skip a runbook entry ("we'll document later" is how silent outages happen).

References

docs/SDLC.md Support

Next step hint

After writing the gate file, pipe the next_suggestions conditions to skills/_shared/next-hint.sh and print any output:

printf '%s\n' \
  'support_gate_signed|run /docs to refresh the artifact index and traceability matrix' \
  | bash skills/_shared/next-hint.sh

Print any output verbatim. If the script outputs nothing, add nothing.