FlowBench
[EMNLP 2024] FlowBench: Revisiting and Benchmarking Workflow-Guided Planning for LLM-based Agents
This repository contains the source data and code for our EMNLP 2024 paper FlowBench: Revisiting and Benchmarking Workflow-Guided Planning for LLM-based Agents. We propose a comprehensive benchmark, FlowBench, for workflow-guided agent planning. We first revisit and formalize different workflow knowledge formats for agent planning. FlowBench covers an extensive taxonomy (6 domains, 22 roles, 51 scenarios) and different knowledge formats (text, code, flowchart) to synchronize with real-world applications comprehensively.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/justherozen-flowbench — read its card at https://meshkore.com/agent/justherozen-flowbench/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/justherozen-flowbenchFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/justherozen-flowbench/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own FlowBench?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.