spec-first-interview

分类: 工具与效率 | 上传者: marlandoj | 下载: 0 | 版本: v1.0（最新）

Socratic interview and seed specification generator. Use before any major build task to clarify requirements, expose hidden assumptions, and produce an immutable spec ("seed") with acceptance criteria and an ontology. Prevents wasted cycles on ambiguous work. Adapted from Q00/ouroboros.

更新日志: Source: GitHub https://github.com/marlandoj/zouroboros-seedkit

目录结构

当前层级: skills/spec-first-interview/

📁 references/
- 📄 ontologist.md 1.5 KB
- 📄 seed-architect.md 1.5 KB
- 📄 socratic-interviewer.md 2.5 KB
📁 scripts/
- 📄 interview.ts 7.8 KB
📄 SKILL.md 4.7 KB

SKILL.md

---
name: spec-first-interview
description: >
  Socratic interview and seed specification generator. Use before any major build
  task to clarify requirements, expose hidden assumptions, and produce an immutable
  spec ("seed") with acceptance criteria and an ontology. Prevents wasted cycles
  on ambiguous work. Adapted from Q00/ouroboros.
compatibility: Created for Zo Computer
metadata:
  author: marlandoj.zo.computer
  origin: https://github.com/Q00/ouroboros
---

# Spec-First Interview

> Before telling AI what to build, define what should be built.

## When to Use

- Before any multi-step build task (new skill, service, site, agent workflow)
- When a request is vague or has implicit assumptions
- Before committing expensive LLM cycles to implementation
- When multiple personas will collaborate on a deliverable

## Quick Start

```bash
# Run the interview
bun Skills/spec-first-interview/scripts/interview.ts --topic "Build a webhook retry system"

# Generate a seed spec from interview notes
bun Skills/spec-first-interview/scripts/interview.ts seed --from /path/to/interview-notes.md

# Score ambiguity of a request
bun Skills/spec-first-interview/scripts/interview.ts score --request "Make the site faster"
```

## Workflow

### Phase 1: Socratic Interview

Adopt the **Socratic Interviewer** role (see `references/socratic-interviewer.md`).

1. **Start with the broadest ambiguity source** — ask one focused question
2. **Build on each answer** — reference earlier responses, probe inconsistencies
3. **Track three dimensions** as you go:
   - Goal clarity (weight 40%)
   - Constraint clarity (weight 30%)
   - Success criteria clarity (weight 30%)
4. **After 5–8 questions**, compute ambiguity:
   ```
   ambiguity = 1 - (goal × 0.40 + constraints × 0.30 + success × 0.30)
   ```
5. **Gate**: Interview passes when ambiguity ≤ 0.2 (80% clarity)

**Rules during interview:**
- ONLY ask questions — never promise to build, implement, or create anything
- End every response with a question
- No filler ("Great question!", "I understand")
- Use ontological probes: "What IS this?", "Root cause or symptom?", "What are we assuming?"
- If existing codebase context is available, ask confirmation questions citing specific files — not open-ended discovery

### Phase 2: Seed Generation

Once ambiguity ≤ 0.2, adopt the **Seed Architect** role (see `references/seed-architect.md`).

Extract from the interview:

| Component | Description |
|-----------|-------------|
| **Goal** | Clear, specific primary objective |
| **Constraints** | Hard limitations (pipe-separated) |
| **Acceptance Criteria** | Measurable success conditions (pipe-separated) |
| **Ontology** | Domain model — name, description, fields (name:type:description) |
| **Evaluation Principles** | Quality dimensions with weights (name:description:weight) |
| **Exit Conditions** | When to stop (name:description:criteria) |

Save the seed to the workspace as a YAML file:

```yaml
# seed-{id}.yaml
id: seed-{uuid}
created: {iso_date}
goal: "Build a CLI task management tool in Python"
constraints:
  - "Python 3.14+"
  - "No external database"
  - "Must work offline"
acceptance_criteria:
  - "Tasks can be created with title and priority"
  - "Tasks can be listed, filtered by status"
  - "Tasks persist to local JSON file"
ontology:
  name: task
  description: "A unit of work to be tracked"
  fields:
    - name: id
      type: string
      description: "Unique identifier"
    - name: title
      type: string
      description: "Human-readable task name"
    - name: status
      type: string
      description: "Current state: pending | done"
evaluation_principles:
  - name: correctness
    description: "Does it do what was asked?"
    weight: 0.4
  - name: simplicity
    description: "Is the implementation minimal?"
    weight: 0.3
  - name: usability
    description: "Is the CLI intuitive?"
    weight: 0.3
exit_conditions:
  - name: all_ac_met
    description: "All acceptance criteria satisfied"
    criteria: "AC compliance = 100%"
```

### Phase 3: Ontological Check (Optional)

For complex or high-stakes work, run the **Ontologist** lens (see `references/ontologist.md`) on the seed:

1. **Essence** — "What IS this, really?" Strip away accidental properties
2. **Root Cause** — "Is this the root problem or a symptom?"
3. **Prerequisites** — "What must exist first?"
4. **Hidden Assumptions** — "What are we assuming? What if the opposite were true?"

## Integration with Zo Workflows

- **Blog chain**: Run interview before the content-strategist step
- **Swarm campaigns**: Generate a seed, then decompose into campaign tasks
- **Service builds**: Interview → seed → implement → evaluate (see `three-stage-eval` skill)
- **Persona creation**: Clarify role boundaries and responsibilities before creating identity files

登录后下载/点赞/收藏 ❤ 4 | ★ 0

spec-first-interview

目录结构

SKILL.md

举报内容

提示