Agent可靠性评估工具:上下文工程质量是关键指标
// Agents Do Not Fail Alone //
// Agents Do Not Fail Alone //
Very nice open-source eval tool to check agent reliability.
Lots of cool ideas in there.
(bookmark it)
What's the problem?
Context engineering has become central to building reliable agents but it remains almost entirely unmeasured.
Instructions, tools, memory, retrieved knowledge, guardrails, and untrusted inputs all accumulate in the context, and when that gets weak the agent drifts, hallucinates, misuses tools, becomes vulnerable to injection, and burns tokens.
This work validates context-engineering quality as an independent leading indicator of agent reliability. The measurement lives in ProofAgent-Harness, open-source infrastructure that scores context with multi-juror consensus across seven criteria, covering role clarity, guardrail coverage, instruction consistency, tool schema quality, grounding sufficiency, injection hardening, and token efficiency.
The context score is isolated from behavioral metrics and release decisions, so the prediction is not smuggled in. Holding frontier LLM agents fixed and varying only their operating context, each criterion predicts its matching outcome.
Why you want to consider doing these checks:
> Grounding sufficiency predicts hallucination resistance. > Guardrail coverage predicts manipulation resistance. > Tool-schema quality predicts tool use.
Paper: https://arxiv.org/abs/2607.14275
Learn to build effective AI agents in our academy: https://academy.dair.ai/
更进一步:量化金融体系
看懂新闻只是起点——沿量化金融路径,把它变成能交付的工程能力