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Spec driven development

Skill magnus919/agent-skills/spec-driven-development

Curated collection of AI agent skills for Hermes and other agent frameworks

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npx -y skills add magnus919/agent-skills --skill spec-driven-development

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Spec-Driven Development (SDD) methodology for AI software factories — where structured specifications are the input, AI agents generate the code, and quality gates enforce correctness at each pipeline phase. Use when designing a spec → review → decompose → implement → verify pipeline that any AI coding tool (Claude Code, Cursor, Hermes Agent, Devin, OpenHands) can follow.

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SKILL.md

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Spec-Driven Development for AI Software Factories

A methodology for building software where specifications are the executable input to an AI code generation pipeline. The factory model: specs are blueprints, AI agents are the assembly line, verification is quality control, and gates catch defects before they compound.

Pipeline Overview

INCEPTION → [SPECIFY] → REVIEW → [DECOMPOSE] → REVIEW → [IMPLEMENT] → REVIEW → [VERIFY] → DELIVER
                 ↑         ↑          ↑            ↑           ↑           ↑          ↑         ↓
            Phase 1    Gate 1    Phase 2       Gate 2    Phase 3      Gate 3    Phase 4   Gate 4

Each phase passes through a gate before the next begins. A defect caught at Gate 1 costs minutes to fix; the same defect found at Gate 4 costs hours.

SDD Core Principles

  1. Precision over clarity. A precise-but-dense spec is better than a readable-but-ambiguous one. The AI cannot ask for clarification — it implements one interpretation at random.
  2. Completeness over brevity. Every missing acceptance criterion is a missing feature. Specifying an edge case upfront costs minutes; discovering it in production costs hours or days.
  3. Testability over descriptiveness. An AC that cannot produce CLEAR PASS or CLEAR FAIL is not an AC — it's a hope.
  4. Gates catch defects early. A Gate 1 (spec review) fix costs minutes. A Gate 4 (acceptance review) fix costs hours — the entire implementation may need to be discarded.
  5. Spec is the single source of truth. Every downstream artifact traces back to the spec. Deviations are defects unless explicitly documented.
  6. Spec IS the test (when possible). Gherkin-style ACs serve double duty as test cases. No separate test writing required.

Loading Guide

ReferenceLoad whenFile
SDD Overview & PhilosophyYou need to understand the why — the software factory metaphor, how SDD differs from traditional requirements, the core principle that specs are executable inputs not communication artifactsreferences/sdd-overview.md
The AI Factory PipelineYou need the full 5-phase pipeline with phase inputs, outputs, and transition rules — or you're designing a new pipeline from scratchreferences/ai-factory-pipeline.md
Spec Quality GatesYou've written a SPEC.md and need to validate it before Gate 1 — the 7 gates that separate a good spec from a vague onereferences/spec-quality-gates.md
Phase Gate MethodologyYou're running a review gate (any of the 4) and need the decision criteria, verdict format, and escalation pathreferences/phase-gate-methodology.md
Methodology Selection MatrixYou're deciding which spec methodology (BDD, Formal, DbC, OpenAPI, ADRs) fits your context — when each applies and their AI-readiness ratingsreferences/methodology-matrix.md
NFR Encoding for AI SpecsYou need to express non-functional requirements (performance, security, observability) in machine-readable formatreferences/nfr-encoding.md
Format TranslationYou need to map between spec formats — Gherkin ↔ OpenAPI ↔ SPEC.md ↔ JSON Schema — or translate a human PRD into an AI-ready specreferences/format-translation.md
Critiques & TradeoffsYou need to decide when not to use SDD — the honest limitations: spec bottleneck, GIGO, drift, over/under-specification, the formal methods taxreferences/critiques-and-tradeoffs.md
Worked Example — Complete SPEC.mdYou want to see a fully-realized specification to calibrate your output depth — shows proper AC format, edge case enumeration, NFR thresholds, data contracts, and assumptions for a password reset featurereferences/example-spec.md

Methodology Quick-Pick

Not sure which spec methodology fits your situation? Use this quick reference table (load references/methodology-matrix.md for full depth):

ConcernReach ForAI-ReadinessFormat Produces
REST API contractsOpenAPIVERY HIGHYAML/JSON specification
Event/message schemas (Kafka, RabbitMQ)AsyncAPIHIGHYAML/JSON channel specs
Behavioral requirements (what the system does)BDD / GherkinHIGH.feature files with Given/When/Then
Interface correctness (pre/post/invariants)Design by ContractVERY HIGHAssertions in code
Distributed system correctness (consensus, protocols)TLA+ / AlloyVERY HIGH (narrow scope)Mathematical model
Architecture decisions (why we chose X)ADRsMEDIUMStructured markdown
System structure (boxes-and-lines)C4 ModelMEDIUM-HIGHPlantUML / structured text
Raw stakeholder intentUser StoriesLOW (needs refinement)"As a... I want..."

Composite approach: Most systems need 3-4 of these working together. REST APIs get OpenAPI, event streams get AsyncAPI, critical behavior gets Gherkin scenarios, and cross-team interface boundaries get DbC assertions.

Templates

TemplatePipeline PhaseFile
SPEC.mdPhase 1 — Spec Authoring (SPECIFY). Write this first: problem, scope, user stories, ACs, edge cases, NFRs, data contractstemplates/SPEC.md
REVIEW.mdGate 1-4 — Phase-Gate Review. Use at every gate transition: spec review, plan review, implementation review, acceptance reviewtemplates/REVIEW.md
TASK-PLAN.mdPhase 2 — Work Decomposition (DECOMPOSE). Extract from an approved spec: task groups, dependency graph, per-task ACs, implementation directivestemplates/TASK-PLAN.md
VERIFICATION.mdPhase 4 — Verification (VERIFY). After implementation: AC pass/fail matrix, compliance score, failure dossiers with remediationtemplates/VERIFICATION.md

Scripts

ScriptWhen to runFile
spec-quality-check.shAfter writing or editing a SPEC.md — validates all required sections exist (problem statement, scope, ACs, edge cases, NFRs, assumptions)scripts/spec-quality-check.sh
spec-to-tasks.shAfter writing a TASK-PLAN.md — validates every spec AC has a covering task referencescripts/spec-to-tasks.sh

Trigger Conditions

Load this skill when:

  • You're building a software factory — a system where AI agents produce code from structured specifications through a gated pipeline
  • You're designing or refining an AI code generation pipeline where specs drive implementation
  • You need to write a specification that an AI agent (not just a human) will consume
  • You're evaluating spec methodologies (BDD, Formal, OpenAPI-first) for a project
  • You need templates for SPEC.md, TASK-PLAN.md, REVIEW.md, or VERIFICATION.md
  • You're reviewing or verifying AI-generated code against its specification

Quick Reference: Pipeline Steps

StepActionLoad This ReferenceProduces
1Write SPEC.md from template — problem, scope, stories, ACs, edge cases, NFRsreferences/spec-quality-gates.md (validate before Gate 1)SPEC.md
2Run spec-quality-check.sh on SPEC.mdValidation report
3Gate 1 — Review spec against quality gates, produce REVIEW.mdreferences/spec-quality-gates.md, references/phase-gate-methodology.mdREVIEW.md (APPROVED/CONDITIONS/REJECTED)
4Decompose approved spec into TASK-PLAN.md — each task traces to a spec sectionreferences/ai-factory-pipeline.md (Decompose phase)TASK-PLAN.md
5Gate 2 — Review task plan for dependency honesty, spec coveragereferences/phase-gate-methodology.mdREVIEW.md
6Implement each task — one task per agent sessionCode/PR
7Gate 3 — Verify implementation against spec (not code style)references/phase-gate-methodology.mdREVIEW.md
8Run verification against all ACs — produce VERIFICATION.mdVERIFICATION.md
9Gate 4 — Review verification report, deliver only if no BLOCKING failuresreferences/phase-gate-methodology.mdFinal approval

For deeper methodology context, load references/sdd-overview.md (philosophy) or references/ai-factory-pipeline.md (full pipeline detail with parallel execution).

Pipeline Mode & Entry Points

Where to Enter the Pipeline

You don't always start at SPECIFY. Enter at the phase matching what you already have:

You Have ThisEnter AtStart With
A vague idea, conversation, or PRDPhase 1 — SPECIFYtemplates/SPEC.md + references/format-translation.md
Approved product scope with interaction contractsPhase 1 — SPECIFYproduct-design-and-ux handoff + templates/SPEC.md
A clear, approved specificationPhase 2 — DECOMPOSEtemplates/TASK-PLAN.md + references/ai-factory-pipeline.md
A spec + approved task planPhase 3 — IMPLEMENTTask cards with per-task directives
Existing code needing verificationPhase 4 — VERIFYtemplates/VERIFICATION.md

Which Pipeline Mode to Use

Not every change needs all 4 gates. Choose your mode:

ModeWhen to UseGates to RunSpec Depth
FullGreenfield feature, multi-agent work, high-risk change, complex interfacesAll 4 gatesFull SPEC.md with ACs, NFRs, data contracts, edge cases
LightweightSimple bug fix, well-understood change, single-file editGate 1 (light) → Implement → Gate 4 (light)Single user story, 1-3 ACs, abbreviated NFRs
MinimalPrototype, spike, exploration, throwaway codeNone — skip formal gatesMini-spec: 1 paragraph + 3 ACs. No NFR table, no contracts

Rule of thumb: If you know the fix in under 60 seconds and it touches one file, use Lightweight mode. If you're not sure what the right solution is, use Full mode — the gates will catch your mistakes early.

Gate Recovery & Revision

What happens when a gate rejects your artifact? The pipeline doesn't stop — it iterates.

The Revision Loop

Artifact submitted → Gate review → REJECTED or CONDITIONS
                                         ↓
                              Return to current phase
                                         ↓
                              Patch specific findings
                                         ↓
                              Resubmit for re-review
                                         ↓
                              APPROVED → next phase

How to Patch, Not Rewrite

Each finding identifies a narrow, fixable defect. Patch at the finding's location:

Finding SeverityActionExample
BLOCKINGFix immediately — gate cannot pass until resolvedRewrite untestable AC with binary PASS/FAIL condition
CRITICALMust fix. Gate may pass with documented exception if ≤2 findingsAdd missing edge cases to User Stories section
MINORFix before next phase if feasible. Gate can pass with remediation planAdd request/response schemas to Data Contracts
INFONote for future improvement. No action required for gate passSuggestion for alternative field naming

Re-Review Scope

After patching, the reviewer determines scope:

  • Full re-review: Required when REJECTED verdict. The entire artifact is re-evaluated, not just patched sections.
  • Targeted re-review: Possible with CONDITIONS verdict. Only the affected findings and surrounding context are reviewed.

Risk of partial fixes: Fixing only BLOCKING findings and ignoring CRITICAL ones guarantees re-rejection at the same gate. The CRITICAL findings that cost minutes to fix at Gate 1 will cost hours if caught at Gate 4.

Common Revision Patterns

Failure PatternFix StrategyPrevention
Untestable ACs (vague language like "should handle", "should be efficient")Rewrite each AC with explicit Given/When/Then and binary outcomeApply Gate 1 check before submitting
Missing edge casesAdd edge case enumeration per story — 3 minimum per storyUse the "five things that could go wrong" test from spec-quality-gates
Vague NFRs ("should be fast", "should be secure")Replace with specific threshold + verification methodUse the "can I write a test for this?" test from nfr-encoding reference
Incomplete contracts (endpoint listed but no schemas)Add full request/response schemas for every endpointCheck Gate 5 before submitting
Scope creep (ambiguous in-scope items)Tighten scope description and expand Out of ScopeApply the "would someone include more than intended?" test

Tool-Agnostic Design

This skill describes the methodology, not a specific tool. The pipeline works with:

  • Claude Code — use CLAUDE.md as spec context, plan-then-implement mode
  • Cursor — Plan Mode + .cursorrules for spec context, Agent Mode for implementation
  • Hermes Agent — native SDD pipeline (authoring → review → decomposition → verification)
  • Devin / OpenHands — task-based implementation from spec-derived task plans
  • GitHub Copilot Workspace — issue-driven with spec as structured issue body
  • droid (Factory) — task cards from spec decomposition

The templates are format-agnostic (markdown). Adapt the handoff mechanism (CLAUDE.md, .cursorrules, AGENTS.md) to your tool.

Gives 0 of the 12 instructions most quality gates skills give in ~3.1k tokens

Counted across 1,195 of the 2,094 authors here whose files we hold, read 2026-08-07

  • read the output and check the exit codein 54 of 1195, across 14 files
  • verify requirements using a line-by-line checklistin 53 of 1195, across 12 files
  • identify the verification command proving the claimin 51 of 1195, across 12 files
  • run the full verification commandin 50 of 1195, across 11 files
  • verify output confirms the claimin 49 of 1195, across 12 files
  • check version control diff after agent delegationin 46 of 1195, across 6 files
  • state claim with evidencein 44 of 1195, across 4 files
  • run the test suitein 33 of 1195, across 26 files
  • keep state in memory by defaultin 27 of 1195, across 6 files
  • make prototype runnable with one commandin 26 of 1195, across 5 files
  • produce a verification reportin 25 of 1195, across 14 files
  • detect the package manager from lockfilesin 24 of 1195, across 5 files

Said here and by no other author read

  • write the specification first
  • prefer precision over clarity
  • prefer completeness over brevity
  • prefer testability over descriptiveness
  • use acceptance criteria as test cases
  • run spec quality checks after writing

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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