Decision Log (2026-02-05): OAuth Token Handling Updates and Continued Knowledge Index Sharding

Context#

This update window includes two distinct kinds of activity:

1. A small but security-relevant change to how CI authentication tokens are represented/managed. 2. Ongoing work that expands and reorganizes “knowledge packs,” including continued sharding of indices by Nippon Decimal Classification (NDC) and further evolution of self-recognition guidance content.

This post focuses on decision-relevant impact: what changed, why it matters, and what it enables.

What Changed#

1) CI authentication token representation adjusted#

A configuration used for CI authentication tokens was edited with a small set of additions and deletions.

Why this matters Even small deltas in token configuration can affect:

• Which workflows can authenticate successfully
• Which scopes/permissions are available during CI execution
• The stability of downstream automation that relies on these credentials

Expected impact

• Reduced friction in CI runs that need authenticated access
• Clearer alignment between token configuration and the current automation needs

2) Knowledge indexing continues to shift toward NDC-based shards#

Recent work continues to reorganize indices into NDC shards and refresh associated index metadata.

Why this matters Sharding an index by a classification system like NDC is primarily a retrieval and maintainability decision:

• Smaller, topic-bounded shards can be searched and updated more efficiently
• Classification-aware retrieval supports better “category grounded” answers (e.g., arts vs. history vs. industry)
• Metadata refreshes help keep cataloging and lookups coherent as the corpus grows

User-facing outcome

• More predictable retrieval behavior when queries map naturally to NDC domains
• Reduced cross-topic noise when fetching supporting material for a narrow question

3) Self-recognition guidance content expanded (evaluation + operational modules)#

Recent additions expand self-recognition guidance with an emphasis on:

• Evaluation framing (moving beyond pass/fail into measurable performance tracking)
• Operational considerations (deployment playbooks and governance hooks)
• Legal and regulatory framing (including Japan-specific considerations such as APPI categories and handling of biometric identifiers)

Why this matters Self-recognition in applied settings tends to fail in the gaps between:

• Technical measurement (what metrics exist and what they mean)
• Operational thresholds (what “good enough” means under constraints)
• Governance and compliance (how to document, minimize, retain, and justify processing)

Outcome

• Improved ability to connect measurement (error trade-offs, risk) to action policies and operational decision points
• Stronger alignment between privacy principles (e.g., data minimization and retention discipline) and system design choices

Decision Notes#

Decision: Treat token configuration changes as “high leverage” despite small diffs#

Because authentication governs the reliability of automation, small edits here should be reviewed with disproportionate care relative to their line count.

Decision: Prefer classification-sharded retrieval for scaling knowledge packs#

Continuing the move toward NDC shards reflects a choice to scale retrieval via structured topic partitioning rather than a single expanding monolith.

Decision: Make evaluation and governance first-class alongside model performance#

The direction of the self-recognition materials indicates a decision to treat evaluation protocols and governance hooks as core deliverables, not afterthoughts.

No Changes Detected?#

Not applicable for this date/slot: there is a concrete diff affecting CI token configuration, and contemporaneous work reflects continued movement on knowledge indexing and self-recognition guidance.