Tool · Beta

Bayanat Labs Arabic Agent Reliability Lab

The Arabic Agent Reliability Lab is a local harness that tests Arabic AI agents in a synthetic commerce sandbox and grades their tool calls and final state, not how finished the answer sounds. It is a methods beta: the code is Apache-2.0, and the open scenarios and the published evidence receipts are CC BY 4.0.

By Bayanat Labs· Updated · Apache-2.0· اقرأ بالعربية
LicenceApache-2.0 (code); CC BY 4.0 (open scenarios and receipts)
Versionv0.2.0 · Harness and open scenarios v0.2.0; published evidence receipts v0.1 (methods beta).
Published
Updated
Who it is forTeams building Arabic tool-using agents who need to check what the agent actually did, not what it said.
LevelAdvanced

Arabic AI agent evaluation tool-use evaluation state-based agent testing Arabic agent reliability evidence receipts

Key numbers

21synthetic workflow families
3fixed-setting repeats per family
4disclosed runs, including a rule baseline

Counted by script from the released files. No MANIFEST.json exists for this release, which predates the open-data programme. Each key number is computed from the released receipts file and pinned to its SHA-256.

Downloads and identifiers

WhereWhat
GitHubCode on GitHub
bayanatlabs.comEvidence receipts (JSON)
bayanatlabs.comReceipts checksum (SHA-256)
ZenodoZenodo archive (all versions) 10.5281/zenodo.23355782

Get started

Run it locally

# Python 3.12 and uv; the rule agent needs no model
git clone https://github.com/Bayanat-Labs/arabic-agent-reliability-lab
cd arabic-agent-reliability-lab
uv sync --extra dev
uv run barl benchmark --agent rule

What is released

PartLicenceIn this release
Harness code and documentationApache-2.0Yes
Open synthetic scenarios (scenarios/open/)CC BY 4.0Yes
Methods-beta evidence receipts v0.1 (receipts.json and checksum)CC BY 4.0Yes
Held-out evaluation material, raw traces and private promptsNot released.No

Attribution: Arabic Agent Reliability Lab by Bayanat Labs. https://www.bayanatlabs.com/research/arabic-agent-reliability

Intended uses

  • Evaluate Arabic tool-using agents by their tool calls and final state, not by how fluent the answer sounds.
  • Inspect and challenge the published evidence receipts against the disclosed run IDs and checksum.
  • Run the harness against your own local models, keeping least-privilege and full-toolset results separate.

Out of scope

  • A leaderboard, a ranking or a statement about Arabic AI overall.
  • A certification, a safety rate or a production-readiness claim.
  • Dialect conclusions: non-MSA prompts have not had dialect-matched native review.
  • Prompt-injection resistance claims.

Rights at a glance

Training, display, redistribution and synthetic-voice use are separate permissions.

UseStatusNote
TrainingAllowedOpen scenarios and receipts under CC BY 4.0, with attribution. Held-out material is not released.
DisplayAllowedWith attribution under CC BY 4.0.
RedistributionAllowedCode under Apache-2.0; open scenarios and receipts under CC BY 4.0. The Bayanat Labs name and logo are not licensed.
Synthetic voiceNot applicableNo audio.

Limitations

  • All cases are synthetic, open development cases in one commerce sandbox; they do not establish production performance.
  • The public receipts use Modern Standard Arabic only.
  • Fixed-setting repeats are diagnostic repetitions, not independent evidence of general reliability.
  • Scores describe whole-system configurations, not the underlying model in isolation.
  • English renderings are editorial aids, not certified translations.

Sources and licences

No third-party data. The scenarios and receipts are synthetic and describe a fictional commerce business. Models under test are named in the receipts with their versions and digests. Source details

Findings we state

Methods beta for state-based evaluation of Arabic agents in an open synthetic sandbox (21 workflow families) with evidence receipts. "A fluent answer is not a completed transaction." (as of 5 October 2026; see the claims register)

How to cite

Cite as:

Bayanat Labs (2026). Arabic Agent Reliability Lab (v0.2.0) [Software]. Zenodo. https://doi.org/10.5281/zenodo.23355783
@software{bayanat2026agentlab,
  author    = {{Bayanat Labs}},
  title     = {Arabic Agent Reliability Lab},
  version   = {v0.2.0},
  year      = {2026},
  month     = oct,
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.23355783},
  url       = {https://doi.org/10.5281/zenodo.23355783}
}

How we handle citations

Changelog

DateVersionChange
v0.2.0Harness and open scenarios released on GitHub and archived on Zenodo with a DOI.
v0.1Methods beta with three evidence receipts and a checksum published on bayanatlabs.com.

Corrections and removal requests

If something in this release should not be there, or is wrong, email hello@bayanatlabs.com. We handle removal requests within 30 days, and platform requests within 24 hours. How removal requests work

Full write-up: Arabic Agent Reliability Lab on bayanatlabs.com

Related product: Bayanat Agents

Need production-grade, rights-cleared data?

We publish synthetic fixtures, open benchmarks, results, code and guides for free. Data at scale is licensed or built to order: ready-to-license Arabic speech and text datasets with commercial AI-use rights written into the agreement, and custom collection, annotation and evaluation.

Bayanat Agents: Train agents to look things up, make changes, and check that the job is done. License Arabic agent trajectories or build executable tasks around your APIs and business rules.