Oleks 38e1adbd48 Phase 4: boundary rubric skill, offload-analyst agent, calibration gate
references/boundary-rubric.md is design/rubric.md verbatim (4.1).

skills/boundary-rubric is usable standalone on a single step before any code
exists — the rubric is more valuable applied before the fact than after (4.2).

agents/offload-analyst classifies pre-computed inventory/scan JSON, leads with
coverage, treats hook/prose drift as its own category, and enforces the hard
gate: no overrule case -> boundary question, never filed (4.3).

bin/boundary-classify applies rubric §6's confidence table and the FR-4.2 filing
gate. The determinism-test outcomes and the falsifiability triple are inference;
grading them is a lookup, so it is a script rather than agent prose (FR-8.1).

Calibration gate (4.4) passes on real runs:
  - token-budget            -> 0 high-confidence, "nothing to offload here"
  - worktree-discipline with bin/worktree-audit masked out
                            -> worktree-safety classification at high,
                               position llm-over-script-digest

tests/classify.test.sh asserts both gates plus synthetic table cases; 67
assertions green across the suite.
2026-07-29 17:27:17 +03:00

inference-arbitrage

Audits a Claude Code plugin — its skill/agent definitions and its real usage transcripts — to find steps that are being done by raw LLM inference but pass every test of a deterministic script, and files the well-evidenced ones as issues on the target plugin's own repo. Runs on demand; each run accumulates into a snapshot history so cost and candidate status can be tracked over time.

The name echoes builder-arbitrage: route each unit of work to the cheapest executor that can do it correctly — here, "script vs. model" instead of "which build node."

Status: scaffolding, pre-implementation. See design/ for the full specification:

Tracked as issues on this repo under the v0.1.0 milestone.

S
Description
Claude Code plugin — optimize Claude model selection by routing inference requests to the best model per query, balancing cost, latency, and accuracy.
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