Self-Recognition Knowledge Expansion, NDC Sharding, and Desktop Universe Workflow Maturation

Context #

This update clusters around three threads that reinforce each other:

1) expanding “self-recognition” guidance content (especially around evaluation validity, failure modes, and privacy/legal routing), 2) reorganizing knowledge indexing into Nippon Decimal Classification (NDC) “shards” to improve retrieval precision, and 3) maturing the desktop “universe” workflow—both the editor experience and execution pipeline—alongside broader Windows support.

The net effect is a tighter loop between: (a) what the system *knows* (structured packs and desires), (b) how that knowledge is *retrieved* (NDC-aware indexing/assignments), and (c) how users *apply* it (desktop universe tooling and sample workflows).

What Changed #

1) Self-recognition knowledge packs evolved #

The knowledge base added and refined content focused on avoiding category errors in mirror/self-recognition discussions and making evaluations more auditable. Key themes visible in the retrieved evidence include:

Clear separation of behavioral evidence vs. cognitive inference (e.g., discouraging claims that a subject/system is “self-aware” based solely on a behavioral marker).
Structured evaluation guidance for mirror self-recognition, including phase-based execution and explicit negative/boundary checks.
Failure taxonomy framing to label “why” a test failed (environmental/perceptual issues, interaction misunderstandings, etc.) rather than collapsing everything into a single pass/fail metric.

In parallel, the knowledge expansion also deepened biometric processing compliance decisioning across jurisdictions:

Jurisdiction routing before activation/collection (defaulting to a strict posture when the region is unknown).
Biometric data categorization alignment, including Japan’s APPI treatment of biometric identifiers as personal identifier codes, and GDPR special category constraints.
Consent and record-keeping patterns emphasizing minimization and retention discipline rather than “store everything just in case.”

2) NDC sharding and assignment structure strengthened #

Indexing work reorganized knowledge retrieval around NDC “shards,” making it easier to target the right conceptual neighborhood when searching or assembling context.

The retrieved material shows NDC coverage spanning:

700 (Arts / Fine Arts) with sub-areas like art theory, art history, painting, photography, crafts, and related subdivisions.
600 (Industry) as a home for operational playbooks and organizational deployment concerns.
210 (History of Japan) to contextualize institutional history and trust/consent norms.

This matters because self-recognition systems often mix disciplines (UX/environmental design, organizational procurement, legal compliance, and evaluation methodology). NDC sharding provides a consistent way to “pin” content so retrieval doesn’t overfit to one domain (e.g., purely technical evaluation) while ignoring others (e.g., environment/UX hazards or operational governance).

3) Desktop universe workflow and editor/execution improvements #

The desktop experience and universe tooling were iterated to support smoother creation, viewing, and execution of “universe” artifacts.

High-level shifts implied by the evidence:

Editor and viewer UX improvements (including language/editor refinement and general desktop UI polish).
Execution pipeline adjustments to better run and validate universe definitions.
Broader Windows support, including explicit attention to Windows distribution/executable handling.

4) Sample universe flows added/expanded #

A substantial set of sample “universe flow” materials appeared, covering multiple creative/production-like workflows (for example, manga/music-oriented samples with contexts, steps, deliverables, and run checkpoints).

These samples serve two purposes:

Demonstrate how to structure a workflow into inputs, plans, acceptance criteria, deliverables, and iterative checkpoints.
Stress-test the editor/viewer/executor loop with realistic, multi-step content.

Why It Matters #

Higher-quality retrieval: NDC sharding + assignments reduces ambiguity when different disciplines share overlapping vocabulary (e.g., “recognition,” “identity,” “mirror,” “verification”).
Safer claims and reporting: The self-recognition guidance explicitly pushes teams to report observed behaviors and test conditions without over-claiming mental states.
Operational readiness: The compliance routing and retention/minimization framing help prevent deploying biometric/self-recognition features with incomplete jurisdiction assumptions.
Better end-to-end usability: Desktop universe improvements and sample flows make it easier to go from “idea” → “structured workflow” → “execution and iteration,” instead of treating workflows as static documentation.

Outcome / Impact #

Taken together, these changes move the system toward a more complete “knowledge-to-action” loop:

knowledge packs articulate evaluation rigor and compliance constraints,
NDC sharding makes that knowledge more retrievable and correctly scoped,
desktop universe tooling provides a practical surface to apply and iterate workflows,
sample flows provide concrete patterns and reusable structure.

Notes on Repository State #

There are local, uncommitted changes present (a small update affecting CI authentication token configuration) and newly generated draft blog artifacts in the working directory. Those artifacts indicate active documentation/reporting work, but the core product-facing changes are best understood through the knowledge expansion, indexing reorganization, and desktop universe workflow maturation described above.