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18. Success Criteria

aDNA Specification v2.5 Section 18 of 20 Full text

Scan: Three levels — minimum viable (cold start, handoff, integrity), recommended (fork, scale, consistency), aspirational (network, collision safety, dual-audience).

Decisions: D21

flowchart TB
    subgraph MIN["Minimum Viable (MUST)"]
        M1["Cold Start"]
        M2["Handoff"]
        M3["Integrity"]
    end

    subgraph REC["Recommended (SHOULD)"]
        R1["Fork"]
        R2["Scale"]
        R3["Consistency"]
    end

    subgraph ASP["Aspirational"]
        A1["Network"]
        A2["Collision Safety"]
        A3["Dual-Audience"]
    end

    MIN -->|mature| REC
    REC -->|excellent| ASP

    style MIN fill:#22c55e,color:#fff
    style REC fill:#3b82f6,color:#fff
    style ASP fill:#8b5cf6,color:#fff

18.1 Minimum Viable (every aDNA MUST pass)

  1. Cold Start: A fresh agent reads CLAUDE.md, then STATE.md (if present), and begins useful work within one session. No prior project knowledge is required.
  2. Handoff: Agent A closes a session with SITREP + next-session prompt. Agent B reads the close-out and STATE.md and continues the work seamlessly.
  3. Integrity: No data corruption or silent overwrites during multi-agent operation with collision prevention active.
  1. Fork: The aDNA structure can be copied to a new project and adapted with only CLAUDE.md and domain content changes.
  2. Scale: The aDNA supports 10+ missions, 50+ sessions, and 100+ content files without navigational degradation.
  3. Consistency: Both deployment forms (bare and embedded) feel like the same system to agents and humans.

18.3 Aspirational (excellent aDNA)

  1. Network: Multiple aDNA instances can discover and reference each other via documented patterns.
  2. Collision Safety: Multi-agent concurrent operation produces no data loss even under heavy write contention.
  3. Dual-Audience: Both humans (IDE, GitHub, knowledge-base tools) and agents find the content navigable and useful.