Chi Bench Fiable Agent — Data skill for Claude Code

fiable-agent

Reliability by construction for long-horizon healthcare agents on χ-Bench

*fiable* (Spanish): reliable, trustworthy.

[](LICENSE) [](pyproject.toml) [](tests) [](https://github.com/actava-ai/chi-bench) [](https://www.kaggle.com/competitions/chi-bench)

Overview

**fiable-agent** is our entry to the [IEEE Big Data Cup 2026 — Challenge 07: χ-Bench](https://www.kaggle.com/competitions/chi-bench). χ-Bench asks an autonomous agent to drive real-world U.S. healthcare-administration cases — provider prior authorization, payer utilization management and population care management — to the correct terminal state inside χ-World, a high-fidelity simulator of healthcare applications exposed as MCP tools and governed by a 1,279-document Managed-Care Operations Handbook.

The benchmark scores with a **strict binary verifier**: a trial earns 1 only when *every* required deterministic contract check and every rubric-judged policy check passes. The organisers rank by **pass@1**, then by **pass³** (all three independent attempts must pass), then by cost and tool calls.

That scoring rule shapes our whole design. In the χ-Bench paper the strongest agent reaches 28.0 % pass@1 and no agent exceeds 20 % pass³ ([arXiv:2605.16679](https://arxiv.org/abs/2605.16679)). Many failures are not clinical misjudgements but *avoidable workflow slips*: a decision submitted without its rationale, a case fin