Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add magnus919/agent-skills --skill spec-driven-developmentgit clone --depth 1 https://github.com/magnus919/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/magnus919/agent-skills/spec-driven-development)<a href="https://agentmods.dev/skills/magnus919/agent-skills/spec-driven-development"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/spec-driven-development.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00165 | $0.03528 |
| Opus 5 | $0.00082 | $0.01764 |
| Sonnet 5 | $0.00033 | $0.00706 |
| Haiku 4.5 | $0.00016 | $0.00353 |
Grade A, and why
spec-driven-development scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 |
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 7.5 KB
- README.md 1.6 KB
- references/ai-factory-pipeline.md 5.3 KB
- references/critiques-and-tradeoffs.md 6.5 KB
- references/example-spec.md 7.8 KB
- references/format-translation.md 7.3 KB
- references/methodology-matrix.md 6.5 KB
- references/nfr-encoding.md 5.8 KB
- references/phase-gate-methodology.md 4.7 KB
- references/sdd-overview.md 4.3 KB
- references/spec-quality-gates.md 5.2 KB
- scripts/spec-quality-check.sh 2.9 KB runs code
- scripts/spec-to-tasks.sh 2.3 KB runs code
- templates/REVIEW.md 945 B
- templates/SPEC.md 2.2 KB
- templates/TASK-PLAN.md 2.3 KB
- templates/VERIFICATION.md 2.2 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 214 lines · 165 tokens per session scan A 7ec40a49b55d
spec-driven-development is a skill published in the GitHub repository magnus919/agent-skills (74 stars, last pushed today), licensed MIT. It adds 165 tokens to every session and 3,528 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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fix-bug
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test-driven-development
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
test-driven-development
TDD: enforce RED-GREEN-REFACTOR, tests before code.