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Delivery · Version 1.1.0 · Reviewed 2026-08-02

Database Release Coordinator

Make a defensible decision about schema rollout sequencing and backfill coordination with evidence, explicit trade-offs, and a verification plan.

4 method steps 6 documented failure modes 5 diagnostic checks 7 quality gates

Coordinates application and database releases through expand-migrate-contract phases, online backfills, compatibility checks, and irreversible-step gates.

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What this skill helps you do

  • Schema rollout sequencing
  • Backfill coordination
  • Compatibility verification

How Database Release Coordinator works

You provide

Schema, query plans, and the real access pattern

It inspects

Plan accuracy and lock behavior for schema rollout sequencing

It decides

A backfill coordination change weighed against write cost

You verify

Re-measured plan with buffer reads and timing compared

What it checks first

Database Release Coordinator coordinates application and database releases through expand-migrate-contract phases, online backfills, compatibility checks, and irreversible-step gates. Use it when the work involves Schema rollout sequencing, Backfill coordination, Compatibility verification.

  1. The actual query plan with real row counts, not the estimated plan or the query text alone.
  2. Whether the workload is read-heavy, write-heavy, or mixed, since the correct design differs sharply.
  3. Transaction boundaries and duration, because long transactions block vacuum and hold locks.
  4. Index coverage relative to both the filter and the sort, since satisfying one but not the other still costs a sort.
  5. Connection pool behavior, as pool exhaustion presents as database slowness while the database is idle.

Failure modes it recognizes

  • An index that serves the predicate but not the ordering, forcing a full sort for a small LIMIT.
  • A long-running transaction preventing vacuum and causing gradual bloat and plan degradation.
  • Implicit type casting on a join or filter column silently disabling index use.
  • Connection pool exhaustion from long-held connections, appearing as a database problem.
  • A write-heavy table with excessive indexes where insert cost dominates the workload.
  • Statistics stale after a bulk load, so the planner chooses a plan for a table size that no longer exists.

Answers it will reject

  • Adding an index per slow query until write amplification becomes the new bottleneck.
  • Tuning configuration parameters before examining the plan for the dominant query.
  • Interpreting `EXPLAIN` without `ANALYZE`, which reports estimates and proves nothing.
  • Increasing pool size to fix latency caused by lock contention, which adds waiters rather than capacity.

Decision rules it applies

  • Optimize the query that dominates total time, not the one that feels slowest in isolation.
  • Order composite index columns by equality first, then range or sort last.
  • Keep transactions short and never hold one open across an external call.
  • Create and drop indexes concurrently on live tables, accepting the longer build for the absent lock.

Evidence it asks for

  • `EXPLAIN (ANALYZE, BUFFERS)` to compare estimated with actual rows and attribute I/O.
  • Rank queries by cumulative execution time rather than by single-execution latency.
  • Monitor the oldest open transaction and lock wait counts as standing metrics.

The method inside

  1. Establish what is actually true about schema rollout sequencing from the supplied evidence, and mark what is missing.
  2. Identify the mechanism behind backfill coordination rather than restating the symptom.
  3. Choose the smallest defensible change for compatibility verification, weighing impact, confidence, effort, and reversibility.
  4. Record consequences, rollback, and open questions

Deliverables

  • Schema rollout sequencing assessment
  • Backfill coordination decision and action plan
  • Compatibility verification verification checklist

Evidence requirements

  • Functional and quality requirements
  • Scale, latency, consistency, cost, and compliance constraints
  • Current topology and alternatives considered

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Coordinate a release that changes a primary identifier type while old and new application versions may run together for several hours.

Expected output

Introduce the new identifier alongside the old one, dual-write with reconciliation, backfill in resumable batches, switch reads only after parity checks, and delay the destructive contract step until every old binary is outside rollback windows...

Boundaries and compatibility

Ideal for

  • Schema rollout sequencing: produce a decision or artifact grounded in supplied evidence.
  • Backfill coordination: produce a decision or artifact grounded in supplied evidence.
  • Compatibility verification: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Producing a generic reference architecture without requirements
  • Hiding material trade-offs behind best-practice language

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.