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Architecture · Version 1.4.0 · Reviewed 2026-08-02

gRPC Contract Designer

Make a defensible decision about message evolution and streaming selection with evidence, explicit trade-offs, and a verification plan.

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

Designs protobuf messages, field numbering, streaming choices, and deadline propagation for evolvable services.

₹99 one-time

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What this skill helps you do

  • Message evolution
  • Streaming selection
  • Deadline propagation

How gRPC Contract Designer works

You provide

Obligations, data inventory, and current controls

It inspects

Requirement type and implemented control for message evolution

It decides

A streaming selection gap register with accountable owners

You verify

Each control mapped to evidence an auditor would accept

What it checks first

gRPC Contract Designer designs protobuf messages, field numbering, streaming choices, and deadline propagation for evolvable services. Use it when the work involves Message evolution, Streaming selection, Deadline propagation.

  1. Whether the obligation is a legal requirement, a contractual commitment, or an internal policy — the escalation path differs.
  2. The specific data categories and lawful basis, rather than a general statement about compliance.
  3. Data flows across jurisdictions and processors, which determine transfer obligations.
  4. Retention and deletion behavior in every downstream copy, including backups and analytics.
  5. Who is accountable for the decision, since a compliance analysis without an owner is not actionable.

Failure modes it recognizes

  • Deletion implemented in the primary store while copies persist in backups, exports, logs, and warehouses.
  • Consent collected for one purpose and reused for another without a valid basis.
  • A subprocessor added without a data-processing agreement or customer notification.
  • Retention policy defined but never enforced by an automated job.
  • A control documented in policy but not implemented in the system it describes.

Answers it will reject

  • Providing a definitive legal conclusion rather than a structured analysis for qualified review.
  • Treating a compliance certification as evidence that a specific control works.
  • Relying on contractual language to mitigate a technical risk that is technically preventable.
  • Presenting risk without severity, likelihood, and the accountable owner.

Decision rules it applies

  • Separate legal requirement, contractual obligation, and internal policy in every finding.
  • Escalate to qualified counsel for anything that constitutes legal advice, and say so plainly.
  • Map every obligation to a specific implemented control and its evidence, or mark it as a gap.
  • Prefer technical enforcement over documented intent, because documented intent is not a control.

Evidence it asks for

  • Build a data inventory: category, source, purpose, basis, location, retention, and downstream copies.
  • Trace one deletion request end to end and enumerate every store it must reach.
  • Record the evidence artifact that would satisfy an auditor for each control.

The method inside

  1. Turn message evolution into explicit functional requirements and quality-attribute constraints.
  2. Model the critical path, state, trust, and failure boundaries that govern streaming selection.
  3. Compare viable designs for deadline propagation against weighted constraints and operational ownership.
  4. Select a design with consequences, rollout stages, observability, and a reversible adoption path.

Deliverables

  • Message evolution assessment
  • Streaming selection decision and action plan
  • Deadline propagation 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

Design a gRPC contract for a service that returns large result sets and must stay backward compatible for two years.

Expected output

Large result sets argue for server streaming rather than a single response, because a unary call forces the whole set into memory on both sides. Reserve removed field numbers explicitly, never reuse them, and treat every field as optional so old clients keep parsing new messages...

Boundaries and compatibility

Ideal for

  • Message evolution: produce a decision or artifact grounded in supplied evidence.
  • Streaming selection: produce a decision or artifact grounded in supplied evidence.
  • Deadline propagation: 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.