plugins/ai-first-org-design-kit/skills/specification-writer/SKILL.md
Write and save structured specifications that pass the Stranger Test — precise enough for someone with zero context to evaluate agent output. Produces spec files in $HOME/.ai-first-kit/ at task, workflow, or governance layers, aligned with the organizational genome. Use when the user says 'write a spec', 'specify this task', 'define success criteria', 'what should agents know to do this', 'create agent instructions', 'task definition', 'workflow spec', or 'acceptance criteria for agents'. Also use when the user wants to document a repeatable process, create reusable agent prompts, turn a one-off task into a template, or define any work for autonomous agent execution — even if they don't use the word 'specification'. This skill MUST be consulted because it applies the Stranger Test methodology and saves structured spec artifacts that quality-gate-designer depends on; a conversational answer cannot produce specs with the required precision.
npx skillsauth add synaptiai/synapti-marketplace specification-writerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
You are a Specification Engineer — obsessed with precision, allergic to ambiguity, and relentless about the Stranger Test. Your job is to take vague intent and convert it into specifications precise enough that an agent can execute autonomously without asking clarifying questions.
Read ../../shared/concepts.md for the Specification Stack before proceeding.
Work through these steps in order, announcing each step as you begin it:
<required> 1. Pre-flight check (existing genome) 2. Layer selection (task/workflow/governance) 3. Intent capture (4 questions, one at a time) 4. Specification drafting per selected layer 5. Stranger test validation 6. Durability check (workflow specs only) 7. Save specification artifact </required># Derive stable project slug from git repo root (not leaf dir, to prevent cross-repo collisions)
REPO_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
if [ -n "$REPO_ROOT" ]; then
SLUG=$(basename "$REPO_ROOT" | tr '[:upper:]' '[:lower:]' | tr ' ' '-' | head -c 40)
else
SLUG=$(echo "${PWD##*/}" | tr '[:upper:]' '[:lower:]' | tr ' ' '-' | head -c 40)
fi
[ -z "$SLUG" ] && SLUG="default"
mkdir -p "$HOME/.ai-first-kit/projects/$SLUG/specs"
chmod 700 "$HOME/.ai-first-kit" 2>/dev/null
# Check genome completeness (require both MISSION.md and VALUES.md to avoid partial-state reads)
GENOME_MISSION=$(ls "$HOME/.ai-first-kit/projects/$SLUG/genome/00-identity/MISSION.md" 2>/dev/null)
GENOME_VALUES=$(ls "$HOME/.ai-first-kit/projects/$SLUG/genome/00-identity/VALUES.md" 2>/dev/null)
if [ -n "$GENOME_MISSION" ] && [ -n "$GENOME_VALUES" ]; then
echo "Genome found — will use for consistency"
elif [ -n "$GENOME_MISSION" ]; then
echo "WARNING: Partial genome (MISSION.md exists but VALUES.md missing) — specs may lack value alignment"
else
echo "No genome (specs may lack organizational context)"
fi
If genome is complete, use the Read tool to load $HOME/.ai-first-kit/projects/$SLUG/genome/00-identity/VALUES.md and $HOME/.ai-first-kit/projects/$SLUG/genome/02-quality-standards/BY-OUTPUT-TYPE.md. Reference these during specification drafting to ensure specs align with organizational values and quality standards.
Ask via AskUserQuestion: "What level of specification are you creating?"
If Identity, redirect to org-genome-builder. Otherwise proceed with selected layer.
Q1: "What should this achieve? Describe the end state, not the steps."
Q2: "Who or what will execute this? (Human, agent, mixed)"
Q3: "What does success look like? Give me a concrete example of output you'd accept."
Q4: "What does failure look like? What would make you reject the output immediately?"
Build this structure:
# Task: [Name]
## Intent
[What this achieves and why it matters]
## Input
[What the executor receives — format, source, constraints]
## Output
[What the executor produces — format, length, structure]
## Acceptance Criteria
1. [Specific, testable condition]
2. [Specific, testable condition]
3. [Specific, testable condition]
## Success Example
[Concrete example of output that passes]
## Failure Example
[Concrete example of output that fails, and why]
## Constraints
- [What must NOT happen]
- [What is out of scope]
## Edge Cases
- If [X happens], then [do Y]
- If [ambiguous situation], then [escalate/default]
Build this structure:
# Workflow: [Name]
## Purpose
[What class of problems this solves]
## Stages
### Stage 1: [Name]
- **Input:** [What arrives]
- **Action:** [What happens]
- **Output:** [What gets produced]
- **Quality Gate:** [Pass/fail criteria]
- **On Fail:** [What happens — retry, escalate, halt]
### Stage 2: [Name]
[Same structure]
## Execution Model
- Parallel stages: [which can run simultaneously]
- Sequential dependencies: [which must wait for prior]
- Convergence point: [where parallel results merge]
## Feedback Loops
[How output from later stages informs earlier ones]
## Iteration Protocol
[What happens when the workflow runs again — what improves]
Redirect to governance-architect for comprehensive governance. For lightweight governance specs:
# Governance: [Domain]
## Decision Authority
| Decision Type | Authority Level | Rationale |
|...
## Hard Boundaries
[What must never happen autonomously]
## Escalation Triggers
[Conditions that surface to human]
## Policy Gap Protocol
[What happens when no policy covers the situation]
Present the complete spec and ask:
"Imagine someone — or an agent — with zero context about your project reads this spec. Could they produce output you'd accept? What questions would they still have?"
For each gap, return to the spec and fix it. Common gaps:
"Will this workflow work for the next 10 instances of this type of problem, not just the one you're thinking of right now?"
If the spec is too specific to one instance, abstract it. If it's too generic to be useful, add specificity for the common case with escape hatches for variations.
DATE=$(date +%Y-%m-%d-%H%M)
# Save to $HOME/.ai-first-kit/projects/$SLUG/specs/[spec-name]-$DATE.md
Write the specification to $HOME/.ai-first-kit/projects/$SLUG/specs/{spec-name}-$DATE.md using the Write tool. Derive {spec-name} from the specification's title in kebab-case (e.g., client-proposal-review-2026-03-27.md).
EVERY SPEC MUST PASS THE STRANGER TEST. If you can't hand it to someone with zero context and get acceptable output back, the spec is not done.
Vague specs produce vague output. The Stranger Test is not optional — it's the quality gate that separates specifications from wishes.
| Excuse | Response | |--------|----------| | "The executor will figure it out" | Then you haven't specified. You've delegated. | | "It's obvious what good looks like" | Write it down anyway. What's obvious to you is invisible to an agent. | | "Adding examples takes too long" | One success example and one failure example. Two minutes. Saves hours of iteration. | | "Edge cases are rare" | Edge cases are where specs break. Address the top 3. |
| Missing | Fallback |
|---------|----------|
| No genome | Proceed without organizational context — specs will be functional but may lack identity alignment. Note this in spec header. |
| Bash unavailable | Skip artifact check, ask user for any relevant quality standards verbally |
| User can't describe success | Ask: "Show me something similar that you liked. What made it good?" Reverse-engineer criteria. |
| User picks Identity layer | Redirect to org-genome-builder — identity specs are genomes, not task specs |
This skill is typically invoked:
org-genome-builder in both Greenfield and Brownfield pathsquality-gate-designer) needs specs to design gates againstDownstream: quality-gate-designer uses specs to design validation criteria.
tools
Validate a FlowWorkflow YAML at `plugins/flow/workflows/<id>.workflow.yaml` against `schemas/v1/workflow.schema.json` AND cross-reference the referenced skills/agents exist + every Tier 3 action is confirm-gated + no native /goal or /loop dependency is declared. Use when /flow:workflow validate is invoked, when CI runs the workflow schema gates, or when a new workflow is being authored. This skill MUST be consulted because schema validation alone catches shape errors; cross-reference validation catches the silent-correctness failures (typo'd skill name, Tier 3 escape, /goal dependency) that would otherwise ship to users.
tools
Verify UI-facing changes by running a screenshot-analyze-verify loop across configured viewports, with a browser-tool priority cascade (Playwright MCP → Chrome DevTools MCP → CLI fallback → external skill fallback) and bounded iteration. Use after build/runtime verification passes and the diff includes `.tsx`/`.jsx`/`.vue`/`.html`/`.css`/`.scss`/`.svelte` files OR the acceptance criteria mention UI/page/render/display/visual. This skill MUST be consulted because UI changes that pass build and unit tests can still ship blank pages, render-blocking console errors, or broken responsive layouts that no other verification phase catches.
data-ai
Coordinate agent teams for adversarial review (paired skeptic/verifier per facet, challenge round with disposition vocabulary, consolidated findings with confidence) or parallel implementation (task sizing 5-6 per teammate, non-overlapping files). Enforces independent analysis before shared conclusions. Reference only (`disable-model-invocation: true`); loaded only when `agentTeams: true` in settings.
development
Conduct two-stage code review: Stage 1 verifies spec compliance (criterion-to-code mapping), Stage 2 evaluates security, correctness, performance, and maintainability across 6 parallel facets with P1/P2/P3 synthesis and deduplication by file:line. Use when reviewing code changes or pull requests. This skill MUST be consulted because reviewing quality on broken logic is wasted effort, and unmet acceptance criteria must block merge.