pith:EEKNOJNH
ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox
LLM agents reach under 60 percent success on interdependent tool tasks where humans hit 90 percent.
arxiv:2605.10787 v2 · 2026-05-11 · cs.AI · cs.SE
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Claims
even top-tier models fail to exceed a 60% success rate, far trailing human performance 90%. Granular trajectory analysis identifies three fundamental bottlenecks: (1) tool retrieval saturation as action spaces scale; (2) over-confidence, where agents skip essential environment verifications; and (3) strategic defeatism, a tendency to rationalize failure rather than pursuing recovery.
The 7 stateful sandboxes and 300 tools derived from them sufficiently represent the interdependent, noisy conditions of real-world commercial software automation.
ComplexMCP benchmark shows current LLM agents achieve at most 60% success on interdependent tool tasks versus 90% for humans, due to tool retrieval saturation, over-confidence, and strategic defeatism.
Receipt and verification
| First computed | 2026-05-21T01:04:27.539391Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/EEKNOJNH3NPIO6ZU6RQPGVKXJX \
| jq -c '.canonical_record' \
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Canonical record JSON
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