PrimeIntellect-ai/verifiers is a library for building environments that train and evaluate large language models. It is used with the Environments Hub, the prime-rl training framework, and Prime Intellect’s Hosted Training platform. Its catalogue add-ons provide coding-agent instructions and skills for working with the library.
Borrowing it
Nothing to install: this file belongs to PrimeIntellect-ai/verifiers. 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/PrimeIntellect-ai/verifiers/main/AGENTS.mdgit clone --depth 1 https://github.com/PrimeIntellect-ai/verifiersWrote 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/primeintellect-ai/verifiers/agents-md)<a href="https://agentmods.dev/instructions/primeintellect-ai/verifiers/agents-md"><img src="https://agentmods.dev/badge/instructions/primeintellect-ai/verifiers/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/primeintellect-ai/verifiers/agents-md"><img src="https://agentmods.dev/badge/instructions/primeintellect-ai/verifiers/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 | $0.00582 | $0.00582 |
| Opus 5.5 | $0.00233 | $0.00233 |
| Sonnet 5.5 | $0.00116 | $0.00116 |
| Haiku 4.5 | $0.00058 | $0.00058 |
Grade A, and why
verifiers 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 3d 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 — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Writing code
- Code is the source of truth: before writing anything, read the v1 code for existing helpers, harnesses, and interfaces instead of reinventing them. Prefer verifiers-native task, trace, server, harness, and runtime interfaces over repeated path/import/discovery plumbing in user packages.
- Minimal config surface: expose as few knobs as possible, but as many as needed.
- Keep tasksets small: a basic taskset fits in a few dozen idiomatic lines — typed data/task/config classes,
load(), and decorated scoring on the task. Don't overrideTaskset.__init__(implementload()); don't overrideHarness.__init__(usesetup()).
Running code
- Always use uv: run code and commands with
uv run, never rawpython. Make sureuvis installed (docs). - Check tasksets: check a taskset without a model with
uv run vf-validate <taskset>. Run a few episodes withuv run vf-run <taskset> -n 1 -r 1. Run full model evals with prime-rl'suv run eval. - Validate TOML first: validate config
.tomlfiles before running them. - Don't add dependencies: never add dependencies or optional extras to the top-level
pyproject.toml.
Docs
- Kept intentionally minimal:
docs/andskills/are deliberately sparse. Don't touch them unless your change breaks their assumptions. - Docs reflect
main, not history: describe the current state of the codebase only — no removed/legacy fields, migration paths, or "this used to be X" anecdotes.
Skills
- Use bundled skills first: the
releaseskill inskills/documents the stable-version release workflow, and thebumpskill documents how to bump a pinned harness version.
Testing
- Two suites:
tests/unitruns one component in isolation;tests/integrationruns real evals (a live model, real runtimes) per behavior across the harness x runtime grid intests/integration/grid.py. Prefer an integration cell over a unit test; a unit test earns its place by stating one component's intended behavior, not by asserting an implementation detail. To check your own work, write a temporary script instead of committing new tests. - Run the contributor checks: run
uv run pre-commit installonce, then for touched areasuv run ruff check --fix .,uv run pytest tests/unit, anduv run pre-commit run --all-files.
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.
- 3d ago Changed · +41 tokens per session ff4aa2a49647
- 18d ago Changed · -6 tokens per session 461502fd3138
- 21d ago Changed · +16 tokens per session ea0542e4bc71
- 23d ago Changed · -44 tokens per session 6e91989bb094
- 1mo ago Changed · +4 tokens per session 214305648757
- 2mo ago Changed · -11 tokens per session 8d02cdfcd5a1
- 2mo ago First seen · 29 lines · 582 tokens per session scan A 54654d4ca04f
verifiers AGENTS.md is an instructions file published in the GitHub repository PrimeIntellect-ai/verifiers (4,769 stars, last pushed yesterday), licensed MIT. It adds 582 tokens to every session, about $0.0023 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.
verifiers AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| verifiers AGENTS.mdPrimeIntellect-ai/verifiers | Instructions file | 4.8k | yesterday | MIT | A | 582 | 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 | yesterday | 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 |