Spec driven development
Curated collection of AI agent skills for Hermes and other agent frameworks
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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
- 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.
- 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.
- Testability over descriptiveness. An AC that cannot produce CLEAR PASS or CLEAR FAIL is not an AC — it's a hope.
- 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.
- Spec is the single source of truth. Every downstream artifact traces back to the spec. Deviations are defects unless explicitly documented.
- Spec IS the test (when possible). Gherkin-style ACs serve double duty as test cases. No separate test writing required.
Loading Guide
| Reference | Load when | File |
|---|---|---|
| SDD Overview & Philosophy | You 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 artifacts | references/sdd-overview.md |
| The AI Factory Pipeline | You need the full 5-phase pipeline with phase inputs, outputs, and transition rules — or you're designing a new pipeline from scratch | references/ai-factory-pipeline.md |
| Spec Quality Gates | You've written a SPEC.md and need to validate it before Gate 1 — the 7 gates that separate a good spec from a vague one | references/spec-quality-gates.md |
| Phase Gate Methodology | You're running a review gate (any of the 4) and need the decision criteria, verdict format, and escalation path | references/phase-gate-methodology.md |
| Methodology Selection Matrix | You're deciding which spec methodology (BDD, Formal, DbC, OpenAPI, ADRs) fits your context — when each applies and their AI-readiness ratings | references/methodology-matrix.md |
| NFR Encoding for AI Specs | You need to express non-functional requirements (performance, security, observability) in machine-readable format | references/nfr-encoding.md |
| Format Translation | You need to map between spec formats — Gherkin ↔ OpenAPI ↔ SPEC.md ↔ JSON Schema — or translate a human PRD into an AI-ready spec | references/format-translation.md |
| Critiques & Tradeoffs | You need to decide when not to use SDD — the honest limitations: spec bottleneck, GIGO, drift, over/under-specification, the formal methods tax | references/critiques-and-tradeoffs.md |
| Worked Example — Complete SPEC.md | You 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 feature | references/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):
| Concern | Reach For | AI-Readiness | Format Produces |
|---|---|---|---|
| REST API contracts | OpenAPI | VERY HIGH | YAML/JSON specification |
| Event/message schemas (Kafka, RabbitMQ) | AsyncAPI | HIGH | YAML/JSON channel specs |
| Behavioral requirements (what the system does) | BDD / Gherkin | HIGH | .feature files with Given/When/Then |
| Interface correctness (pre/post/invariants) | Design by Contract | VERY HIGH | Assertions in code |
| Distributed system correctness (consensus, protocols) | TLA+ / Alloy | VERY HIGH (narrow scope) | Mathematical model |
| Architecture decisions (why we chose X) | ADRs | MEDIUM | Structured markdown |
| System structure (boxes-and-lines) | C4 Model | MEDIUM-HIGH | PlantUML / structured text |
| Raw stakeholder intent | User Stories | LOW (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
| Template | Pipeline Phase | File |
|---|---|---|
| SPEC.md | Phase 1 — Spec Authoring (SPECIFY). Write this first: problem, scope, user stories, ACs, edge cases, NFRs, data contracts | templates/SPEC.md |
| REVIEW.md | Gate 1-4 — Phase-Gate Review. Use at every gate transition: spec review, plan review, implementation review, acceptance review | templates/REVIEW.md |
| TASK-PLAN.md | Phase 2 — Work Decomposition (DECOMPOSE). Extract from an approved spec: task groups, dependency graph, per-task ACs, implementation directives | templates/TASK-PLAN.md |
| VERIFICATION.md | Phase 4 — Verification (VERIFY). After implementation: AC pass/fail matrix, compliance score, failure dossiers with remediation | templates/VERIFICATION.md |
Scripts
| Script | When to run | File |
|---|---|---|
spec-quality-check.sh | After 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.sh | After writing a TASK-PLAN.md — validates every spec AC has a covering task reference | scripts/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
| Step | Action | Load This Reference | Produces |
|---|---|---|---|
| 1 | Write SPEC.md from template — problem, scope, stories, ACs, edge cases, NFRs | references/spec-quality-gates.md (validate before Gate 1) | SPEC.md |
| 2 | Run spec-quality-check.sh on SPEC.md | — | Validation report |
| 3 | Gate 1 — Review spec against quality gates, produce REVIEW.md | references/spec-quality-gates.md, references/phase-gate-methodology.md | REVIEW.md (APPROVED/CONDITIONS/REJECTED) |
| 4 | Decompose approved spec into TASK-PLAN.md — each task traces to a spec section | references/ai-factory-pipeline.md (Decompose phase) | TASK-PLAN.md |
| 5 | Gate 2 — Review task plan for dependency honesty, spec coverage | references/phase-gate-methodology.md | REVIEW.md |
| 6 | Implement each task — one task per agent session | — | Code/PR |
| 7 | Gate 3 — Verify implementation against spec (not code style) | references/phase-gate-methodology.md | REVIEW.md |
| 8 | Run verification against all ACs — produce VERIFICATION.md | — | VERIFICATION.md |
| 9 | Gate 4 — Review verification report, deliver only if no BLOCKING failures | references/phase-gate-methodology.md | Final 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 This | Enter At | Start With |
|---|---|---|
| A vague idea, conversation, or PRD | Phase 1 — SPECIFY | templates/SPEC.md + references/format-translation.md |
| Approved product scope with interaction contracts | Phase 1 — SPECIFY | product-design-and-ux handoff + templates/SPEC.md |
| A clear, approved specification | Phase 2 — DECOMPOSE | templates/TASK-PLAN.md + references/ai-factory-pipeline.md |
| A spec + approved task plan | Phase 3 — IMPLEMENT | Task cards with per-task directives |
| Existing code needing verification | Phase 4 — VERIFY | templates/VERIFICATION.md |
Which Pipeline Mode to Use
Not every change needs all 4 gates. Choose your mode:
| Mode | When to Use | Gates to Run | Spec Depth |
|---|---|---|---|
| Full | Greenfield feature, multi-agent work, high-risk change, complex interfaces | All 4 gates | Full SPEC.md with ACs, NFRs, data contracts, edge cases |
| Lightweight | Simple bug fix, well-understood change, single-file edit | Gate 1 (light) → Implement → Gate 4 (light) | Single user story, 1-3 ACs, abbreviated NFRs |
| Minimal | Prototype, spike, exploration, throwaway code | None — skip formal gates | Mini-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 Severity | Action | Example |
|---|---|---|
| BLOCKING | Fix immediately — gate cannot pass until resolved | Rewrite untestable AC with binary PASS/FAIL condition |
| CRITICAL | Must fix. Gate may pass with documented exception if ≤2 findings | Add missing edge cases to User Stories section |
| MINOR | Fix before next phase if feasible. Gate can pass with remediation plan | Add request/response schemas to Data Contracts |
| INFO | Note for future improvement. No action required for gate pass | Suggestion 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 Pattern | Fix Strategy | Prevention |
|---|---|---|
| Untestable ACs (vague language like "should handle", "should be efficient") | Rewrite each AC with explicit Given/When/Then and binary outcome | Apply Gate 1 check before submitting |
| Missing edge cases | Add edge case enumeration per story — 3 minimum per story | Use 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 method | Use 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 endpoint | Check Gate 5 before submitting |
| Scope creep (ambiguous in-scope items) | Tighten scope description and expand Out of Scope | Apply 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.