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Authoring standalone and cross-team specifications: PRD/SRS/HLD/LLD, staged L0-L4 unified packages, BDD acceptance criteria, and traceability. Use for technical or multi-audience documentation; not implementation or architecture decisions.

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referenceunified-specunified-template.md

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Unified Specification Template

Purpose: Use this file when writing the canonical cross-functional package with L0, L1, L2, L3, and Meta.

Contents

  • Structure overview
  • Audience reading paths
  • Canonical template
  • Quality gates
  • Glossary pattern

Structure Overview

L0: Vision
L1: Requirements
L2-Biz: Business Context
L2-Dev: Technical Design
L2-Design: Design Specification
L3: Acceptance Criteria
Meta: Management

Audience Reading Paths

  • Business: L0 -> L1 -> L2-Biz -> L3
  • Development: L0 -> L1 -> L2-Dev -> L3
  • Design: L0 -> L1 -> L2-Design -> L3
  • Alignment review: L0 -> L3

Canonical Template

# [Project / Feature Name]

## L0: Vision

### Problem (Why)
[Describe the current pain in 1-3 sentences.]

### Target Users (Who)
| Persona | Role | Main pain |
|---|---|---|
| [Name] | [Role] | [Pain] |

### Success Metrics (KPI)
| Metric | Current | Target | Measurement |
|---|---:|---:|---|
| [KPI] | [Current] | [Target] | [Method] |

### Scope
**In**
- [Item]

**Out**
- [Item]

### Timeline
| Milestone | Target date |
|---|---|
| Spec aligned | YYYY-MM-DD |
| Build complete | YYYY-MM-DD |
| Release | YYYY-MM-DD |

## L1: Requirements

### User Stories

#### US-001: [Story title]
**As a** [persona], **I want to** [action], **so that** [value].
**Priority:** Must / Should / Could / Won't
**Linked REQs:** REQ-001, REQ-002

### Functional Requirements

#### REQ-001: [Requirement title]
- **Description:** [detail]
- **Input:** [input]
- **Output:** [expected result]
- **Constraints:** [constraints]
- **Priority:** Must / Should / Could / Won't
- **Linked:** US-001, DESIGN-001, AC-001

### Non-Functional Requirements

| Category | Requirement | Target |
|---|---|---|
| Performance | [Requirement] | [Number] |
| Security | [Requirement] | [Standard] |
| Accessibility | [Requirement] | [WCAG level] |
| Compatibility | [Requirement] | [Browser/device] |

### MoSCoW Priority Matrix
| Priority | Requirements | Reason |
|---|---|---|
| Must | REQ-001 | [Reason] |
| Should | REQ-002 | [Reason] |
| Could | REQ-003 | [Reason] |
| Won't | REQ-004 | [Reason] |

## L2-Biz: Business Context

- Market opportunity
- Competitive context
- Business impact
- Risks and dependencies
- Stakeholders
- Go-to-market

## L2-Dev: Technical Design

- Architecture overview
- API design
- Data model
- Constraints and trade-offs
- Dependencies
- Migration plan when relevant

## L2-Design: Design Specification

Scribe defines flow, interaction, and accessibility requirements only.
Visual artifacts belong to Vision or Palette.

- User flows
- Interaction patterns
- Component usage
- Accessibility requirements
- Responsive behavior

## L3: Acceptance Criteria

### BDD Scenarios

#### AC-001: [Scenario title] — Linked: REQ-001
**Given** [precondition]
**When** [action or event]
**Then** [expected result]

#### AC-002: [Scenario title] — Linked: REQ-001
**Given** [precondition]
**And** [additional precondition]
**When** [action or event]
**Then** [expected result]
**And** [additional expected result]

#### AC-003: [Edge case] — Linked: REQ-002
**Given** [abnormal precondition]
**When** [abnormal action]
**Then** [error handling]

### Edge Case List
| Case | Input | Expected behavior | Linked REQ |
|---|---|---|---|
| [Case] | [Input] | [Behavior] | REQ-XXX |

### Traceability Matrix
| REQ | User Story | Design | BDD Scenario | Test |
|---|---|---|---|---|
| REQ-001 | US-001 | DESIGN-001 | AC-001, AC-002 | - |

## Meta: Management

### Document Metadata
| Field | Value |
|---|---|
| Status | Draft / Review / Approved / Deprecated |
| Version | v0.1 |
| Created | YYYY-MM-DD |
| Last updated | YYYY-MM-DD |
| Author | [Name] |

### Version History
| Version | Date | Change | Author |
|---|---|---|---|
| v0.1 | YYYY-MM-DD | Initial draft | [Name] |

### Review And Approval
| Team | Reviewer | Status | Date |
|---|---|---|---|
| Business | [Name] | Pending / Approved / Rejected | - |
| Development | [Name] | Pending / Approved / Rejected | - |
| Design | [Name] | Pending / Approved / Rejected | - |

### Open Questions
| ID | Question | Owner | Status |
|---|---|---|---|
| Q1 | [Question] | [Owner] | Open / Resolved |

Quality Gates

L0

  • problem is concrete
  • personas feel real
  • KPI is measurable
  • Out is explicit
  • one-page limit is respected

L1

  • every story includes value
  • every REQ has a unique ID
  • every REQ has priority
  • non-functional requirements use measurable targets
  • MoSCoW is explicit

L3

  • every REQ has at least one linked AC
  • happy path and edge cases both exist
  • Given/When/Then uses concrete, testable outcomes
  • traceability matrix is not empty
  • all three teams can understand the scenarios

Glossary Pattern

Use a glossary when one concept is named differently by each team.

## Glossary
| Term | Business meaning | Development meaning | Design meaning |
|---|---|---|---|
| [Term] | [Definition] | [Definition] | [Definition] |

L4 — Reversibility / Learning / Disqualification (SKILL.md excerpt)

These three fields convert acceptance criteria from "what passes" into "how we know it failed and what we recover/learn from it". Phase 1 recommended (advisory if missing), Phase 2 mandatory gate (block merge if missing). Per Magi v4 C6.

Schema:

L4:
  reversibility:
    classification: HIGH | MEDIUM | LOW
    # HIGH = revert via single config flag / single-commit revert / no data migration
    # MEDIUM = revert requires coordinated rollback + data migration window
    # LOW = revert is essentially a new project (schema change, public API change, data loss)
    revert_procedure: <single-paragraph or pointer to runbook>
    revert_time_estimate: <minutes | hours | days>
    revert_blast_radius: <users / services / data affected>

  learning:
    hypothesis: <one-sentence explicit hypothesis the feature tests>
    success_threshold:
      metric: <metric name>
      value: <numeric threshold>
      window: <observation window, e.g. "+30 days post-launch">
    fail_threshold:
      metric: <same or different metric>
      value: <numeric threshold below which feature is failing>
      window: <observation window>
    learning_capture_plan:
      win_capture: <what we record / who, on success — feeds Insight Ledger via tome>
      loss_capture: <what we record / who, on failure — feeds Friction Ledger via trace/voice>
      decision_horizon: <date by which Go-deeper / Modify / Sunset decision is made>

  disqualification:
    # Magi v4 DA-1 finding: "失格条件" (disqualification criteria) machine-readable enforce
    # If ANY disqualification condition triggers, the AC is automatically FAIL (not advisory)
    conditions:
      - id: DISQ-001
        description: <one-sentence machine-checkable condition>
        check: <reference to test / metric / probe>
        on_trigger: REJECT  # mandatory; no override path except Hot-Fix Fast-Path
      - id: DISQ-002
        ...

Rules:

  • reversibility MUST be present for any L0 Vision change. Missing field = Phase 2 merge block.
  • learning.hypothesis MUST be testable (state a specific metric and direction). Vague hypotheses ("improve UX") are rejected.
  • learning.fail_threshold is mandatory — scribe without explicit failure condition becomes Insight Ledger pollution (Magi v4 Sophia S-4).
  • disqualification.conditions[] lists hard-fail conditions. An scribe with empty disqualification list is allowed but generates a WARNING: no machine-checkable failure path advisory.
  • All three fields feed Phase 3 post-launch Measurement Loop in nexus growth-acceptance recipe (when Org Tier = Enterprise + Step 1+ adopted).

Canonical package shape:

Unified Specification Package: [Feature Name]
  L0: Vision
  L1: Requirements
  L2-Biz / L2-Dev / L2-Design
  L3: Acceptance Criteria
  Meta

Source: SKILL.md on GitHub

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    No security issues were detected. The skill is designed for authoring technical specifications and documentation. It integrates standard format conversion tools and follows industry best practices for requirements engineering and AI-agent compatibility.

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