magnus919_agent-skills/production-excellence/references/discovery-brief.md

Production-Excellence Bundle — Bounded Discovery Brief

Purpose

This brief records the pre-implementation survey of existing production and release skills in the magnus919/agent-skills repository. It establishes what the production-excellence bundle owns, what it routes to, and what it must not duplicate. It satisfies acceptance criterion "A bounded discovery brief compares the bundle with existing production and release skills" (issue #195).

Surveyed skills

Each skill below was inspected before the bundle was authored. For every skill the conclusion is the same: it owns a deep specialist domain and does not own the cross-domain acceptance and handoff layer that assembles evidence into a launch or operational decision.

Skill	What it owns	What the bundle does NOT duplicate
site-reliability-engineering	SLO definition, error budgets, incident response, operational recovery, capacity planning, toil reduction	Incident command, on-call procedures, SLO math, error-budget policy, toil automation
release-engineering	Release pipelines, versioning, promotion, rollout, rollback mechanics, deployment strategies	CI/CD pipeline design, artifact promotion, canary/blue-green mechanics, release-please configuration
platform-engineering	Internal developer platforms, paved roads, service catalogs, infrastructure APIs, Golden Paths	Platform architecture, IDP design, service catalog implementation, infrastructure-as-code
secure-software-engineering	Threat modeling, secure design, security review, vulnerability assessment, trust boundaries	STRIDE/OWASP methodology, security-review procedure, threat-model facilitation
data-engineering	Database operations, ETL/ELT pipelines, data quality, schema migration, storage infrastructure	Pipeline design, dbt patterns, SQL analytical patterns, storage architecture
qa-methodology	Test strategy, regression coverage, CI quality gates, verification planning, test-level taxonomy	Test-case design, regression-suite management, test-automation framework design
verification-methodology	Verification verdicts, boundary labeling, evidence standards, gap declaration	Verification-protocol design, evidence-boundary classification
production-readiness	Risk-scaled evidence packet, go/no-go/defer/exception launch decisions with accountable owners	The 11-category evidence checklist, risk-class assignment, accountable-owner identification
migration-engineering	Safe cross-system migrations — expand/contract, compatibility windows, dual-running, backfills, reconciliation, cutover, deprecation, recovery paths	Migration-strategy design, compatibility-window management, cutover sequencing
resilience-and-recovery	Failure modes, degradation choices, RTO/RPO, restore testing, DR, game days, failover, data integrity, recovery communication	Game-day design, DR-runbook authoring, failover-procedure definition
capacity-and-cost-engineering	Demand/capacity/scaling/utilization models, unit-cost connection to SLO decisions, cost-constrained scenario analysis	Capacity-model construction, cost-attribution accounting, quota/rate-limit engineering
incident-learning	Observed facts, causal hypotheses, contributing conditions, follow-up work mapping, verified closure	Incident-analysis facilitation, causal-hypothesis testing, follow-up-ticket management
product-lifecycle-learning	Expected-vs-observed outcome comparison, assumption/decision updates, continue/improve/harvest/pivot/pause/retire choices	Lifecycle-review facilitation, outcome-comparison analysis

Boundary statement

The production-excellence bundle owns the acceptance and handoff layer:

• Assembling cross-domain evidence (readiness, migration, recovery, capacity/cost, incident-learning) into a single production decision record.
• Running the gate model: go, no-go, defer, exception, escalation — each with conditions, evidence, and accountable owners.
• Producing the operational handoff record for the team that will own the service in production.
• Routing post-launch outcomes into incident-learning and product-lifecycle-learning so that production evidence flows back into decisions.

It does not own any specialist's runbook. It does not own incident command (SRE), release pipeline mechanics (release-engineering), platform architecture (platform-engineering), threat modeling (secure-software-engineering), data pipeline design (data-engineering), or test-strategy design (qa-methodology). It composes them — it never re-derives their methods.

What existing bundles do NOT cover

The four pre-existing bundles were also surveyed:

• neckbeard owns the issue-to-PR delivery journey (9-phase SDLC). It does not own the production acceptance and handoff that happens after delivery.
• workflow-architect owns workflow discovery and skill-bundle generation. It does not own production decision-making.
• tailscale owns the Headscale/Tailscale VPN ecosystem. It is domain-specific networking, not production governance.
• research-and-vault owns the research-to-notes sequence. It is a knowledge workflow, not a production workflow.

None of them fill the gap this bundle fills: the cross-domain evidence assembly and launch/operational decision layer that sits between delivery (neckbeard's phase 9) and ongoing production operations.

Decision: bundle owns the acceptance layer, not the specialists' runbooks

The production-excellence bundle is the thin composition layer that:

1. Reads evidence from the five production-domain specialists (production-readiness, migration-engineering, resilience-and-recovery, capacity-and-cost-engineering, incident-learning).
2. Reads applicable evidence from the existing production specialists (SRE, release, platform, security, data, QA).
3. Assembles that evidence into a gate decision (go/no-go/defer/exception/escalation).
4. Produces an operational handoff record.
5. Routes post-launch learning back into incident-learning and product-lifecycle-learning.

It is deliberately thin. It adds no new methodology beyond the acceptance and handoff contract. Every specialist skill remains the authoritative source for its domain.