specify

A feature-specification guide that turns a rough idea into a reviewed product specification covering context, goals, user stories, acceptance criteria, quality requirements, and success measures.

In plain words
What is it for?
Use it to define a feature's scope, intended users, expected behavior, quality constraints, and measurable outcomes in a spec.md file.
Why use it?
It exposes unclear assumptions and missing requirements before implementation. A Socratic interview means it develops the idea through focused questions and review.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/genkovich/sdd/specify
Any agent
npx skills add genkovich/sdd --skill specify
Clone the repo
git clone --depth 1 https://github.com/genkovich/sdd

Made for: Claude Code, Codex.

Per session 211 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,570 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00211 $0.03570
Opus 5 $0.00105 $0.01785
Sonnet 5 $0.00042 $0.00714
Haiku 4.5 $0.00021 $0.00357

Measured 2d ago against content hash 2bc033349922, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

specify scanned grade C with 1 finding 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 2d 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.

Hidden instructionshighPrompt injection

Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.

6. **Read the template + draft §1–§8.** Read [`./templates/spec.md`](./templates/spec.md) (its `<!-- instruction -->` comments are the per-section contract). Draft per [`./references/draft-generation.md`](./references/dr
skills/specify/SKILL.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: specify

Turns a one-line idea into a reviewed spec.md: a lightweight interview captures and stress-tests the idea, then the skill drafts a product spec (context → goals → user stories → acceptance criteria → NFRs → KPIs), validates it Socratically, and runs a clean-context critic before writing. Less typing, more reviewing. This file is the spine; detail lives in references/.

The Socratic machine, the critic, and the size matrix are shared — this skill keeps only its deltas: → ../_shared/socratic-loop.md · ../_shared/critic.md · ../_shared/size-matrix.md · ../_shared/ask-style.md

Depth governs question volume + autonomy (and which ideation analyses run) → ../_shared/interview-depth.md.

Document prose follows the project's artifact_language setting — section headings, frontmatter and machine tokens stay English → ../_shared/artifact-language.md.

Owner

PM + Tech Lead (co-authors). PM drives goals / non-goals / KPIs; Tech Lead drives context patterns and the acceptance-criteria coverage.

Inputs

  • <slug> — kebab-case feature slug.
  • (Optional) CONTEXT.md — the two-level glossary: read both repo-root (project-wide) and docs/features/<slug>/CONTEXT.md (feature-scoped); per-feature wins on conflict → ../glossary/SKILL.md. If present, its roles/terms are canonical and override anything that contradicts them.
  • docs/features/<slug>/.size — depth hint (MVP vs Full per the size matrix). Read if present; established here if absent (step 1 classifies + writes it), so downstream stages never silently default to M. classify-size re-classifies when scope changes.
  • (Optional) prior notes / a reference module / a ticket the user already has.

Protocol

  1. Read context + set interview depth. If a CONTEXT.md exists (read both repo-root and docs/features/<slug>/ — per-feature wins on conflict), load its ## Glossary as session state (canonical roles + terms). If .size exists, read it to size the spec's depth; if it's absent, establish it now — run the classify-size protocol inline (the canon: ../classify-size/SKILL.md + the mapping in ../_shared/size-matrix.md); the four signals fold into one bundled AskUserQuestion here (at easy depth, take the matrix default and record it in the assumptions ledger), and write docs/features/<slug>/.size + .route (the route defaults from the size — XS/S→quick, M→standard, L/XL→full — and is confirmed in the same bundled question, per the Routes table in ../_shared/size-matrix.md) — so every later stage reads a real size instead of silently defaulting to M (the gap that otherwise surfaces only at plan-tests). classify-size stays the utility to re-classify when scope changes. If docs/architecture-map.md exists (from survey), read it so the spec is architecture-aware — it informs §1 Context, §2 Constraints, and §3 Non-goals (what the existing system already does / can't do). Absent → suggest running survey first, but proceed (the spec is product-level and can be captured without it). Do not leak the map's tech into §5 AC — AC stay business-observable; the map shapes constraints, not acceptance criteria. Then set the interview depth (the opening question): if .claude/sdd.local.md is absent, auto-create it with the documented default frontmatter (every key + its allowed values explained inline) and patch .gitignore../implement/references/settings.md; then read interview_depth from it (else default medium), and — unless a --depth=easy|medium|hard arg was passed (which skips the question) — ask ONE depth-selection AskUserQuestion phrased per ../_shared/ask-style.md, with the saved/medium value as the «(Recommended)» first option, overridable per run. The chosen level governs the step-2 deep-dive volume, the step-3 ideation suite, and the step-7 Socratic volume → ../_shared/interview-depth.md. (Completeness — §5's 5-type AC floor — is unaffected by depth.)
  2. Capture the idea (interview front). One AskUserQuestion for the raw idea in 1–3 sentences (persist verbatim as the baseline). Then a Socratic deep-dive across problem clarity / success criteria / constraints / strategic fit, delivered in batches of 2–3 — its volume scales with the depth dial (easy: only the few un-inferable ones, then a stated-assumptions ledger; medium: 3–5; hard: walk every angle, foreground each trade-off). Phrase every question per ../_shared/ask-style.md.
  3. Ideation suite (depth-gated, named subagents). Run the ideation analyses as named-subagent dispatches gated by the interview-depth dial (size as a secondary trimmer) → ./references/ideation.md: easy → skip the suite (deep-dive only; the chosen approach is recorded as a ledger assumption); mediumresearcher (sdd:researcher, competitive/web) + devils-advocate (sdd:devils-advocate, failure-mode mode); hard → full suite researcher + strategist (sdd:strategist, 3 approaches) + analyst (sdd:analyst, multi-perspective) + devils-advocate, then the Claude-proposed RICE/feasibility confirm. Analyses stay product-level (no tech names — that's design); the confirmed recommendation becomes §1 ¶3. Dispatch with subagent_type: "sdd:<name>" per ../_shared/agent-roster.md (general-purpose fallback); researcher needs web — accept its RESEARCH_LIMITED output as a noted gap if web is unavailable.
  4. Reconcile the glossary in-flow (a hard rule, at every depth). On every new or unknown domain term that surfaces in the interview or the draft, invoke glossary <slug> for it immediately — compare it against CONTEXT.md and add/update the definition before continuing. By the time the spec is written, every §4 role and §5 domain term is already glossary-canonical; the glossary is never a deferred batch. (Plan-mode nuance: still decide add/update per term in-flow; if writes are blocked until the spec write-point, persist the reconciled terms together with the spec, but never skip the per-term compare.)
  5. Ask which extra channels to read (multi-select AskUserQuestion): reference module code / project docs / MCP-Atlassian (Confluence/Jira) / knowledge-base / none. For each picked channel ask the specific path/query — no silent broad scans.
  6. Read the template + draft §1–§8. Read ./templates/spec.md (its <!-- instruction --> comments are the per-section contract). Draft per ./references/draft-generation.md: per-section sources, the 5 AC coverage types (happy / error / authorization / domain invariant / cross-context), and the stack-agnostic forbidden-token rule for acceptance criteria.
  7. Socratic validation. Walk §4 US → §5 AC → §6 NFR → §7 KPI with the shared 4-state machine (per-decision question volume scales with the depth dial — at easy, the un-asked decisions land in the assumptions ledger for a batch veto). Specify delta → ./references/socratic.md: AC has a 5th option «Add another AC»; the §5 coverage gate enforces two floors after drops/OQ-migrations — (a) ≥1 AC of each of the 5 coverage types, and (b) ≥1 AC per retained §4 user story (regenerate/add a replacement if a type or a user story is left empty). Both are floors, not dials — enforced at every depth; only the question volume scales. The (b) floor closes the §4→§5 link so the downstream sequences use-case coverage + review trace can't be undermined by a user story that lost its only AC. Maintain the edits-log.
  8. Critic + write + commit. Dispatch the critic agent — subagent_type: "sdd:critic" (model per judgment_model, effort highxhigh on L/XL via CLAUDE_CODE_EFFORT_LEVEL; clean-isolated context per ../_shared/agent-roster.md) — with the specify delta in ./references/critic.md (over ../_shared/critic.md) — inline the draft + edits-log, it Reads CONTEXT.md + the idea source itself. Resolve findings via AskUserQuestion (Accept revert / Accept amendment / Override-with-rationale → §1 ¶4 bullet). Run the forbidden-token regex scan as the F6 backstop. On pass, write docs/features/<slug>/spec.md (glossary already reconciled in-flow per step 4) and propose commit spec: <slug>. Register on the roadmap: in docs/roadmap.md (via roadmap) set the matching step's Status: spec'd and link this feature folder; no matching step → append one (source anchor = this spec). (If there's no roadmap yet, skip — it's optional.) Then emit the stage-handoff block per ../_shared/handoff.mdWhat I did + Review (spec.md, .size, .route) + Run nextresolve the next stage per .route (the Routes table in ../_shared/size-matrix.md; route-resolved variant in handoff.md): forward /sdd:clarify <slug>; clarify's N/A condition = zero §8 open questions and no AC flagged ambiguous, skip target /sdd:ux-flows <slug> (on quick — auto-skip with the reason + inverted ↳ or; on standard — offer the ↳ or; on full — no skip line). When clarify is legally skipped, carry the next condition forward: evaluate ux-flows' N/A condition too (no human-facing UI — every §4 actor a system/service, or the repo has no UI at all, per ../_shared/size-matrix.md) → holds ⇒ the skip target becomes /sdd:design <slug>. (If critic is unavailable, fall back to a general-purpose Agent with the same delta.)

Read the full file on GitHub · 78 lines

Files

What ships with it

5 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.

Changes

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.

  1. 2d ago First seen · 78 lines · 211 tokens per session scan C 2bc033349922

Subscribe to this mod's changes

specify is a skill published in the GitHub repository genkovich/sdd (118 stars, last pushed 13d ago), licensed MIT. It adds 211 tokens to every session and 3,570 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

microsoft/vscode · 56 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens