GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
GTA (General Tool Agent) is a benchmark and evaluation framework that assesses general tool agents in both atomic tasks and open-ended workflows.
Good fit when
- Use GTA when you need to evaluate the performance of an agent across long-horizon, open-ended productivity scenarios.
- Leverage GTA for evaluating both the LLM capability (e.g., GPT, Gemini) and the execution harness (e.g., OpenClaw, Manus).
Avoid when
- Avoid using GTA if you are only interested in evaluating short-term tasks without focusing on full workflow outcomes.
- Do not rely exclusively on GTA for assessing performance if the context of your use case differs significantly from productivity workflows that GTA aims to evaluate.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (153d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install GTASimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A benchmark for evaluating general tool agents with a focus on open-ended workflows and atomic tool-use tasks.
Capability facts
- Languages
- python
Source: github.language · Sep 20, 2026
Categories
Tags
README
GTA: General Tool Agent Benchmark and Evaluation Framework [[NeurIPS 2024 D&B] GTA: A Benchmark for General Tool Agents](https://proceedings.neurips.cc/paper files/paper/2024/file/8a75ee6d4b2eb0b777f549a32a5a5c28 Paper Datasets and Benchmarks Track.pdf) [[arXiv 2026] GTA 2: Bench...
For agents
This page has a .md twin and JSON over the API.