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labrat-operator

labrat-operator is a skill for Claude Code, Codex from ProjectDXAI/labrat. It costs 42 tokens per session (816 once invoked), scanned A, original, MIT.

A set of operating instructions for running a labrat lab, an automated software research workspace that tests and evaluates candidate implementations.

In plain words
What is it for?
It helps diagnose the lab, inspect its status, select the next phase prompt, manage cycles, audit candidates, summarize evaluations and maintain checkpoint notes.
Why use it?
It provides a repeatable way to check the lab, choose the next task, supervise runtime cycles, review candidates and keep coordination notes aligned with the runtime’s records.

Skill for Claude CodeCodex

not rated 239 27d ago A scan 42 tokens original MIT
View the source file ProjectDXAI/labrat
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/projectdxai/labrat/labrat-operator
Any agent
npx skills add ProjectDXAI/labrat --skill labrat-operator
Clone the repo
git clone --depth 1 https://github.com/ProjectDXAI/labrat

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for labrat-operator

README.md
[![agentmods](https://agentmods.dev/badge/skills/projectdxai/labrat/labrat-operator.svg)](https://agentmods.dev/skills/projectdxai/labrat/labrat-operator)
Your own site
<a href="https://agentmods.dev/skills/projectdxai/labrat/labrat-operator"><img src="https://agentmods.dev/badge/skills/projectdxai/labrat/labrat-operator.svg" alt="Measured on agentmods" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 816 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00042 $0.00816
Opus 5 $0.00021 $0.00408
Sonnet 5 $0.00008 $0.00163
Haiku 4.5 $0.00004 $0.00082

Measured 4d ago against content hash adcacaea3994, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

labrat-operator 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 4d 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.

.agents/skills/labrat-operator/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

labrat Operator

Use this skill from a labrat lab root, identified by branches.yaml, evaluation.yaml, runtime.yaml, and scripts/operator_helper.py.

Codex can load this skill implicitly when a task matches the description, or explicitly when the user references $labrat-operator. Keep this skill focused on lab operation; repo release mechanics belong in the root AGENTS.md.

Cold Start

  1. Run python scripts/operator_helper.py doctor.
  2. Run python scripts/operator_helper.py status.
  3. Read coordination/workspace_map.md.
  4. Read coordination/prioritized_tasks.md.
  5. Run python scripts/operator_helper.py next-prompt --runner codex --phase auto.

If you are operating from the repo root, use the equivalent labrat ... --lab-dir <path> commands.

If both repo-root and lab-local AGENTS.md files are loaded, use the lab-local AGENTS.md for runtime operation and the root AGENTS.md for repo maintenance.

Operation Contract

  • The runtime is authoritative. Do not hand-score candidates or edit state/*.json[l] directly.
  • Do one complete operator loop before returning unless a stop condition fires.
  • Reap stale leases, summarize runtime state, synthesize recent evaluations, dispatch work, lease runnable jobs, execute scripts/run_experiment.py, complete candidates through scripts/runtime.py, and verify the resulting state.
  • Use scripts/evaluator.py and scripts/runtime.py for scoring and promotion.
  • Write durable conclusions to coordination/prioritized_tasks.md, logs/checkpoints/, logs/audits/, or logs/expansions/.

Codex Modes

  • Use GPT-5.5 in Codex for design, audit, frame break, profile authoring, release work, and review when it is available in the user's Codex host.
  • Use Plan mode before broad workflow, docs, scaffold, or profile changes.
  • Use normal execution for routine doctor, status, next-prompt, dispatch, lease, and complete loops.
  • Use Codex review after changes to runtime behavior, scaffolding, prompt contracts, or release metadata.

Read the full file on GitHub · 71 lines

Changes

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.

  1. 4d ago First seen · 71 lines · 0 tokens per session scan A adcacaea3994

Subscribe to this mod's changes

labrat-operator is a skill published in the GitHub repository ProjectDXAI/labrat (239 stars, last pushed 27d ago), licensed MIT. It adds 42 tokens to every session and 816 once invoked, about $0.0002 per session on Opus 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.

Multi-AgentScientificTestingai-agentsautonomous-researchclaude-codeexperiment-managementresearch-automation
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