OpenSpec, Superpowers, and Spec Kit: SDD Patterns
Compare OpenSpec, Superpowers, and GitHub Spec Kit through the practical SDD patterns they share: specs, plans, tasks, tests, review gates, and evidence.
Practical articles for teams using spec-first delivery. The focus is on writing clearer requirements, tightening review loops, and shipping with fewer surprises.
Filter by topic, then scan four focused entries per page. Start with the article that matches your current delivery risk, then continue through the related routes below.
Compare OpenSpec, Superpowers, and GitHub Spec Kit through the practical SDD patterns they share: specs, plans, tasks, tests, review gates, and evidence.
A copy-ready packet for giving AI coding tools a bounded task, acceptance criteria, file ownership, tests, and review evidence before code generation starts.
Same order refund feature built two ways — vibe coding ships fast but drowns in edge-case bugs,…
20 real-world acceptance criteria examples in Given/When/Then format covering authentication, e-commerce, APIs, data processing, payments, and notifications.
How to write a technical specification: a complete template, real-world walkthrough, section-by-section guidance, and a free online generator to draft your own.
A practical guide to building test harness infrastructure for backend API services — from fixtures and mocks to contract tests and CI integration,…
Superpowers is an open-source framework that enforces spec-first discipline on AI coding agents.
Define backward compatibility rules for API specs, including deprecation timelines, migration paths, Sunset headers, and breaking-change review.
Define database schemas before writing migrations, including columns, constraints, indexes, API alignment, and rollout order.
AI coding tools drift without constraints — adding fields, renaming functions, expanding scope.
Govern AI-assisted coding with spec-driven prompts: define scope, boundaries, evidence, and audit trails before generated code reaches review.
Review AI-generated pull requests against acceptance criteria: inspect the diff, run evidence checks, and catch failures a quick skim misses.
Use a pre-merge risk register for AI-generated code: flag auth, data, contract, migration, rollback, and observability risks.
Use test-evidence gates for AI-generated code: require meaningful tests before merge and catch hallucinated implementations before release.
Manage API changes for AI-generated clients with structured changelogs, announcement channels, compatibility rules, and CI gates.
Design API error taxonomies AI-generated clients can use, with stable codes, retry categories, and machine-readable details.
How to run an API schema diff review before every release: what diff tools catch, what they miss, and the human checks that still matter for OpenAPI and GraphQL.
Design API specs for LLM-powered agentic clients with discoverable fields, idempotency, dry-runs, semantic descriptions, and safe destructive actions.
Follow a vague support ticket as it becomes a shippable technical spec using Spec Skills, guided questions, and review-ready output.
See how Spec Skills fits spec-first delivery through constrained prompts, spec injection, boundary enforcement, and reviewable AI output.
Quality gates for AI-assisted code: pre-prompt spec checks, diff review, test evidence, and human sign-off before generated code ships.
How to spec real-time collaboration: OT vs CRDT, presence protocol, offline edits, conflict resolution, and the operational transform vs three-way-merge decision.
Add contract testing from OpenAPI to CI with generated tests, provider checks, consumer expectations, and reliable fixtures.
Specify cross-service data sync with ordering guarantees, conflict handling, backfill plans, and event-driven or pull-based tradeoffs.
How to specify idempotency keys, deduplication windows, and state-machine transitions so retries and partial failures don't double-charge or corrupt data.
Specification patterns for event-driven systems: schema versioning, command vs fact events, orchestration choices, idempotent handlers, and replay safety.
Write non-goals that stop scope creep, name deferred work, and give reviewers a clear boundary before implementation starts.
Spec a mobile API for offline mode with local-first writes, sync windows, conflict handling, outbox behavior, and rejection recovery.
Write payment workflow specs with retryable errors, declined-card handling, timeout behavior, 3DS branches, and dunning states.
Design high-risk releases with stop-loss metrics, rollout windows, rollback types, and owners who can pause expansion.
How to write a webhook consumer spec: signature verification, replay protection, retry and backoff rules, ordering assumptions, and idempotent handler design.
Write edge cases QA can execute with concrete inputs, starting states, expected outputs, and release-blocking priority.
Avoid ten specification mistakes that hide decisions, blur acceptance criteria, skip failure paths, and push scope arguments into implementation.
A 30-day adoption plan for Spec-First: choose the first workflow, set a review threshold, and measure whether rework drops.
Turn software requirements into testable specs with observable outputs, failure paths, evidence types, and QA-ready acceptance criteria.
PRD vs Technical Spec: What's the Difference becomes clearer when the team makes the hidden decisions visible before coding starts.
Use this pre-coding review checklist to separate blockers from preferences, record accepted risks, and attach test evidence before implementation begins.
What is spec-first development? A complete guide to surfacing hidden decisions about scope, contracts, edge cases, and acceptance criteria before coding starts.
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Use this as the orientation piece if you want the overall model, tradeoffs, and where spec-first work pays off.
Read the full guideA complete template, worked example, and free generator covering acceptance criteria, edge cases, and the sections every spec needs.
Open the template guideIf you are moving beyond a solo trial, this gives you a concrete rollout rhythm and measurement model.
See the 30-day planPick the path that matches the problem in front of you. Each path starts with a practical article, then points toward a template, checklist, or tool you can use in the same session.
Start with the complete guide, then compare spec-first with agile and use the adoption plan only after the team agrees on the behavior you want to protect.
Start the foundations pathUse the technical spec guide, acceptance criteria examples, and edge-case articles when a ticket is too broad for implementation.
Follow the writing pathStart here when a change touches external consumers, database shape, idempotency, compatibility, or release safety.
Follow the contract pathStart with a spec packet, then move into prompts, risk registers, PR review gates, and test evidence before generated code reaches production.
Follow the AI pathUse these hubs when you want a structured route through the library instead of one article at a time. Each hub includes a decision table, copy-ready block, and related guides.
Start here for the method, core decisions, review gates, and evidence habits.
Open hubUse this route for schema diffs, compatibility, versioning, webhooks, and deprecation.
Open hubTurn success statements into testable criteria with failure paths and proof.
Open hubConnect prompts, risk registers, acceptance mapping, and test evidence.
Open hub