kirk_score_book

io.github.UlyssesModel/kirk-mcp · Verify this server

Score one L2 order-book snapshot through the sealed single-layer path and return a scalar entropy plus engine attestation. Purpose: Score one snapshot end-to-end through the sealed engine and surface the result plus the engine sha that produced it. Use when: You are validating Kirk on your own data before committing to a production path, or you are scoring a single snapshot inside an interactive workflow (rate-limited at 60 req/min per account). Do not use when: You need throughput above interactive scale, or you are in a per-book loop from an LLM. MCP round-trip is millisecond-scale and inappropriate for latency-critical work. For >200 books, call kirk_bulk_howto first — the returned stdlib Python client scores at zero LLM tokens per iteration. Capability class(es): - C2 (variable-universe cross-section entropy scoring — same model handles any N without retraining). - C5 (sealed engine sha stamped on every response). - C6 (bit-exact reproducibility across substrates; validated by the FY24 252-day reproduction, byte-identical on repeat runs). Path fit: Validation via MCP (this tool). Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options. MCP is a validation and discovery surface, not a latency-critical production path. Cost: 1 IU per call. LLM tokens accrue on top for agent-driven callers.