LLM candidate re-ranker — Act 1 SCOPE filter (T446)
An optional one-call sonnet-tier filter that runs during LocalBrain.boot() (Act 1 SCOPE).
After the task-text extractor and git co-change ranker assemble a combined ~15-file candidate
set, the re-ranker asks a cheap LLM to return the top-N most task-relevant files, dropping
false positives before the worker reads anything.
Off by default. Enable with CYBERINE_CANDIDATE_RERANK=true. Requires OPENROUTER_API_KEY
or DEEPSEEK_API_KEY. Any LLM failure, timeout, or missing key degrades silently to the
un-reranked candidate list — the worker always gets a useful context pack.
Gate conditions (all must hold to make the LLM call):
CYBERINE_CANDIDATE_RERANK=true- A provider key is configured (
OPENROUTER_API_KEYorDEEPSEEK_API_KEY) - Combined candidate list has more than 3 entries
When any gate condition is not met, candidates pass through unchanged (zero latency, zero cost).
# Enable the re-ranker (uses OpenRouter sonnet or DeepSeek flash)
CYBERINE_CANDIDATE_RERANK=true cyberine run --bg "add re-ranker to LocalBrain.boot()"
# Override top-N (default 5)
CYBERINE_CANDIDATE_RERANK=true CYBERINE_CANDIDATE_RERANK_TOP_N=3 cyberine run --bg "fix the config loader"
# Override the re-ranker model (default: anthropic/claude-sonnet-5 via OpenRouter, or deepseek-v4-flash direct)
CYBERINE_CANDIDATE_RERANK=true CYBERINE_RERANK_MODEL=deepseek/deepseek-v4-flash cyberine run --bg "..."The re-ranker validates LLM output against the input candidate set — hallucinated file paths are silently dropped. Only paths present in the extractor + git-signal output are returned.
Fleet bench — solve rate and dollars per task (kvxah)
cyberine eval bench scores every available worker, and the judged winner, on a versioned suite of coding tasks with programmatic pass/fail. Router eval above compares routing decisions against...
Per-task model variant selection (T60)
Loop workers that expose a variants map in their WorkerProfile run a different model id depending on task tier — the router picks the cheapest capable variant so you don't pay for deep reasoning...