auto-improve — preview, then apply, what abi and abbey would learn

Two local CLIs, one contract: a dry run is the default, and --apply performs only the steps its gate allows. Neither command edits code, skills, or prompts.

abi — abi improve [--apply] [--model <id>] <input>

Run from /Users/donald/sources/repos/abi. It wraps the SEA learn loop (abi-sea run_learn_loop).

• Dry run runs the loop with persist and adapt_router off. It recalls evidence and reports task=, profile=, evidence_count=, audit_passed=, audit_vetoed=, and apply_allowed=, and it writes nothing.
• --apply re-runs the loop with the default config only when audit_passed=true and audit_vetoed=false. Otherwise it prints skipped: and persists nothing, so a rejected completion never becomes evidence.
• It needs a persistent WDBX store and exits 1 without one. For experiments, point ABI_WDBX_PATH at a scratch directory, never the live ~/.abi/wdbx.

./tools/cargo.sh build -p abi-cli
ABI_WDBX_PATH=target/skill-scratch/wdbx target/debug/abi improve "plan next repair"
ABI_WDBX_PATH=target/skill-scratch/wdbx target/debug/abi improve --apply "plan next repair"

abbey — abbey learn improve [n] [--apply]

Run from ~/dev/active/abbey. It reads the last n route records (default 20), the memory reflect report, and train_candidate curation counts.

• Output rows tagged [auto] are applied by --apply. Today the only auto step is promoting recent routes into the activity layer.
• Rows tagged [review] are for a human: routes below 0.6 confidence, duplicate or low-confidence or superseded memories, and candidates missing provenance. --apply never touches them.
• A dry run with no memory store does not create one.

Gotchas

• In abi, run tests and ./tools/check.sh with < /dev/null (an auth test reads stdin).
• abi's improve is the 14th frozen command. Its help, help.json, completion files, and site/index.html chip list are golden-tested, so a change to its wording means updating those files together.
• The abbey help text calls LoRA "Proposed". Neither loop trains weights beyond abi's adaptive router, so do not describe either as fine-tuning.
• skill-loop's review/fix flags are unrelated and unreliable; do not use them as the improvement signal.