chore(v20a): finish the #474 skip — dead score-autopsy components in commands.rs, stale affinity docs

[runyourempire]

The residual this closes

The half of #474 that was skipped because src-tauri/src/commands.rs was claimed by the #471 lane (now merged). Inventory item 3 of the v20a dead-surface sweep, tracked in .claude/plans/PENDING-DECISION.md item 2.

Removed from commands.rs (all structurally dead, same proof classes as #474)

• mcp_score_autopsy "Learned Affinity" component — bd.affinity_mult is pinned 1.0_f32 (pipeline_v2.rs:614), so (bd.affinity_mult - 1.0).abs() > 0.01 could never fire. Pinned-input class.
• mcp_score_autopsy "Anti-Topic Penalty" component — bd.anti_penalty is pinned 0.0_f32 (pipeline_v2.rs:615), so > 0.01 could never fire. Pinned-input class.
• matching_affinities build + "learned_affinities" emit — reads ace_ctx.topic_affinities, which the AD-029 quarantined loader returns empty; always []. Empty-map-read class. The FE render side was already removed in chore(v20a): delete the structurally-dead learned-affinity surfaces (AD-029/AD-030 arc) #474; the autopsy type has no learned_affinities field.
• score_tuning_snapshot's feedback_interaction_count — mislabeled: its value was ace_ctx.topic_affinities.len() (always 0 via the quarantined loader), not a feedback-interaction count. The real feedback_interaction_count concept (scoring-context bootstrap detection, taste-test seeding) is untouched.

commands.rs now has zero topic_affinities references. The capture side (run_background_behavior_decay → apply_behavior_decay) is deliberately untouched — that is v20b operator territory.

Also cleaned

• src/components/ScoreAutopsy.test.tsx — stale learned_affinities fixture line (the interface field was removed in chore(v20a): delete the structurally-dead learned-affinity surfaces (AD-029/AD-030 arc) #474; the fixture carried dead data).
• Two docs still described the retired scoring path as live (discovered while verifying consumers):
  • docs/GETTING_STARTED.md told users scores come from "Topic Affinity: Learned preferences from your interactions" and an affinity/anti-penalty formula. Replaced with the actual scoring inputs (context similarity, interests, stack/deps, freshness/quality).
  • docs/ARCHITECTURE-DETAILED.md — the PASIFA formula's Steps 5–6 (affinity multiplier, anti-topic penalty), the pipeline flow's "Apply affinity multiplier (learned behavior)" step, and the Relevance Judge diagram entry. Replaced with the v20 reality + a pointer to the PASIFA V2 DSL. Capture-side descriptions (tables, interaction writers, decay) are left as-is — they are still true and pending the operator's v20b call.

NO PIPELINE_VERSION bump

Nothing here touches scoring — only presentation surfaces (autopsy JSON, dev-time tuning snapshot) that provably emitted nothing, plus docs. Stored scores cannot differ.

Verification

• cargo fmt clean; cargo test --lib commands:: targeted pass; clippy via pre-push gate
• npx vitest run src/components/ScoreAutopsy.test.tsx — 5/5
• npx tsc --noEmit clean; npx eslint clean on touched TS
• node scripts/check-file-sizes.cjs — no new errors (commands.rs shrank 40 lines)
• grep topic_affinities src-tauri/src/commands.rs — zero hits

🤖 Generated with Claude Code

https://claude.ai/code/session_01LBY5q2MskiKMkTm6NmB49L