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Delivery · Version 1.2.0 · Reviewed 2026-08-02

Release Candidate Coordinator

Make a defensible decision about release candidate assembly and artifact provenance verification with evidence, explicit trade-offs, and a verification plan.

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

Coordinates a release candidate from version selection through artifacts, provenance, smoke tests, approvals, staged rollout, abort signals, and final publication.

₹199 one-time

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What this skill helps you do

  • Release candidate assembly
  • Artifact provenance verification
  • Promotion and rollback decision

How Release Candidate Coordinator works

You provide

Change scope, traffic volume, and current release process

It inspects

Exposure control and abort signal quality for release candidate assembly

It decides

A artifact provenance verification plan staged by blast radius

You verify

Rollback rehearsed against the deployed schema and data

What it checks first

Release Candidate Coordinator coordinates a release candidate from version selection through artifacts, provenance, smoke tests, approvals, staged rollout, abort signals, and final publication. Use it when the work involves Release candidate assembly, Artifact provenance verification, Promotion and rollback decision.

  1. Whether exposure can be changed without a redeploy, which decides how fast a bad release can be stopped.
  2. The promotion signal and whether it can detect harm the error rate cannot see.
  3. Whether rollback remains available after the first irreversible step in the release.
  4. Batch size, since large releases make attribution and rollback disproportionately harder.

Failure modes it recognizes

  • A canary promoted on infrastructure metrics while a business metric silently degrades.
  • A release coupled to a schema change, so rollback stops being possible after the first write.
  • Session affinity sending the same users to the canary, biasing the comparison.
  • A promotion gate on a metric that updates more slowly than the damage accumulates.

Answers it will reject

  • Treating deploy and release as the same event, which removes control over exposure.
  • Promoting because no alert fired, which confuses absence of detection with absence of harm.
  • Shipping a large batch to reduce release overhead, which raises the cost of every failure.

Decision rules it applies

  • Separate deploy from release with a flag so exposure is reversible without a redeploy.
  • Fix the abort criteria and thresholds before the rollout begins.
  • Sequence schema changes so the previous version keeps working throughout.

Evidence it asks for

  • Compare canary and control on a business metric with enough traffic to be meaningful.
  • Rehearse rollback against the deployed schema, not the previous one.
  • Automate abort so promotion does not depend on a human watching.

The method inside

  1. Establish what is actually true about release candidate assembly from the supplied evidence, and mark what is missing.
  2. Identify the mechanism behind artifact provenance verification rather than restating the symptom.
  3. Choose the smallest defensible change for promotion and rollback decision, weighing impact, confidence, effort, and reversibility.
  4. Record consequences, rollback, and open questions

Deliverables

  • Release candidate assembly assessment
  • Artifact provenance verification decision and action plan
  • Promotion and rollback decision 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

Prepare the next release candidate from this branch and produce a go or no-go checklist tied to build artifacts and production guardrails.

Expected output

Build once from the reviewed commit, record artifact digests and provenance, and test the same artifact that will be promoted. The decision gate includes unresolved defects, migration ordering, owner approvals, staged exposure, measurable abort signals, and a verified previous-version rollback...

Boundaries and compatibility

Ideal for

  • Release candidate assembly: produce a decision or artifact grounded in supplied evidence.
  • Artifact provenance verification: produce a decision or artifact grounded in supplied evidence.
  • Promotion and rollback decision: 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 Agent Skills
  • Cursor Agent Skills
  • Claude Code Skills
  • OpenAI Codex Skills
  • JetBrains Junie Skills

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.