GABRIEL is an OpenAI toolkit that turns qualitative text, image, and audio collections into datasets containing measured attributes. Social scientists and data scientists use it to run large-scale GPT-based rating and extraction tasks with batching, retries, checkpoints, and audit trails. The catalogue contains an instruction for using the toolkit with coding agents.
Borrowing it
Nothing to install: this file belongs to openai/GABRIEL. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/openai/GABRIEL/main/AGENTS.mdgit clone --depth 1 https://github.com/openai/GABRIELWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/openai/gabriel/agents-md)<a href="https://agentmods.dev/instructions/openai/gabriel/agents-md"><img src="https://agentmods.dev/badge/instructions/openai/gabriel/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/openai/gabriel/agents-md"><img src="https://agentmods.dev/badge/instructions/openai/gabriel/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.03731 | $0.03731 |
| Opus 5.5 | $0.01492 | $0.01492 |
| Sonnet 5.5 | $0.00746 | $0.00746 |
| Haiku 4.5 | $0.00373 | $0.00373 |
Grade A, and why
GABRIEL AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GABRIEL agent guide
This is the canonical operating guide for coding agents working in this
checkout or writing code that uses GABRIEL. Keep it concise and update it when
public behavior changes. The README explains the package; the tutorial notebook
contains runnable examples; src/gabriel/api.py is the source of truth for
public signatures.
The recommendations below are practical heuristics, not universal rules. They reflect recurring successful workflows and package behavior at the date shown; they may be stale, unavailable in a particular organization, too expensive, or wrong for a specific dataset. User intent, the live API/package, and evidence from a representative pilot take precedence.
Before improvising a workflow, read gabriel_tutorial_notebook.ipynb carefully.
It is the most complete capability map and shows how tasks, modalities, custom
endpoints, checkpoints, visualization, and downstream analysis fit together.
Before writing or running code
- Inspect the actual environment first. Confirm
gabriel.__file__, the installedopenai-gabrielversion, and the live function signature instead of assuming the PyPI package, this checkout, and an old example are identical. - Inspect unfamiliar scripts and inputs before executing them. For a paid run, confirm the row count, prompt count, model, output directory, and expected cost, then pilot a small representative sample before scaling.
- Prefer the public
gabriel.*wrappers. Useawaitin notebooks andasyncio.run(...)in ordinary Python scripts. - Never place API keys, private data, machine-specific paths, or generated research artifacts in committed examples.
Models change: verify them live
Never invent a model slug or copy one blindly from an old notebook. Check the official model catalog, the pricing page, and the models actually provisioned for the user's organization or gateway before overriding a default or publishing a release. Availability, aliases, rate limits, and feature support can vary by organization.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 266 lines · 3,731 tokens per session scan A 242be18b6363
GABRIEL AGENTS.md is an instructions file published in the GitHub repository openai/GABRIEL (446 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 3,731 tokens to every session, about $0.0149 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
GABRIEL AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| GABRIEL AGENTS.mdopenai/GABRIEL | Instructions file | 446 | 3mo ago | Apache-2.0 | A | 3,731 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |