workbench

workbench is a skill for Claude Code, Codex from inclusionAI/AWorld. It costs 33 tokens per session (1,210 once invoked), scanned A, original, MIT.

An optional workflow for managing several possible workspace results with the Workbench command-line tool. It can validate, compare, preserve, or publish candidates when checkpoints or alternatives are useful.

In plain words
What is it for?
Managing candidate artifacts, checkpoint state, local comparisons, and bounded workspace checks when explicitly selected.
Why use it?
It helps keep alternatives and rollback points organized for tasks where comparing multiple results adds value, without adding ceremony to simple work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Managing candidate artifacts, checkpoint state, local comparisons, and bounded workspace checks when explicitly selected.

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Install with agentmods
npx agentmods add skills/inclusionai/aworld/workbench
About the project

AWorld is an agent harness, meaning a framework that coordinates an AI agent’s tools, memory, context, and execution so expert knowledge can be turned into reusable skills and autonomous agents. It is for building domain-specific agent applications and workflows, with the catalogue entries representing skills, agents, and commands that operate within the AWorld ecosystem.

inclusionAI/AWorld · 1,242 stars · on GitHub · aworldagents.com

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.

Any agent
npx skills add inclusionAI/AWorld --skill workbench
Clone the repo
git clone --depth 1 https://github.com/inclusionAI/AWorld

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 workbench

README.md
[![agentmods](https://agentmods.dev/badge/skills/inclusionai/aworld/workbench/github.svg)](https://agentmods.dev/skills/inclusionai/aworld/workbench)
Your own site
<a href="https://agentmods.dev/skills/inclusionai/aworld/workbench"><img src="https://agentmods.dev/badge/skills/inclusionai/aworld/workbench/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.

agentmods 80×15 button for workbench

Your own site · 80×15
<a href="https://agentmods.dev/skills/inclusionai/aworld/workbench"><img src="https://agentmods.dev/badge/skills/inclusionai/aworld/workbench.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,210 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00033 $0.01210
Opus 5.5 $0.00013 $0.00484
Sonnet 5.5 $0.00007 $0.00242
Haiku 4.5 $0.00003 $0.00121

Measured 3d ago against content hash 34999a35cfae, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

workbench 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.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/workbench_runtime/__init__.py, scripts/workbench_runtime/_process_child.py, scripts/workbench_runtime/_process.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

aworld-skills/workbench/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Use Workbench

Workbench is an AWorld-owned candidate-management capability that is bundled but disabled by default. Use it only when it was explicitly selected and multiple candidates, rollback, checkpoint preservation, or measured local comparison provide real value. Direct and low-risk tasks should usually proceed without Workbench ceremony.

Its checks and receipts are agent self-check evidence only. They do not inspect hidden checks, compute task reward, or represent caller/canonical acceptance. Final external evaluation is outside Workbench.

WORKBENCH_* values are optional ordinary environment variables, not a security boundary. Changing them cannot grant access beyond the terminal's existing operating-system permissions and cannot produce canonical verifier or reward evidence. When they are absent, the CLI uses the real current directory as the workspace, puts state in AWorld's external control/state directory, and derives a bounded scope from AWorld task/session identity or a workspace fingerprint. Explicit values remain supported.

Choose the configured AWorld interpreter when present; otherwise python3 launches the CLI and the CLI uses sys.executable:

WORKBENCH_PYTHON="${AWORLD_PYTHON_EXECUTABLE:-python3}"
"$WORKBENCH_PYTHON" /skills/workbench/scripts/workbench.py --help

The CLI exposes no command-line shortcuts for replacing workspace, state, or scope. Workbench never infers outputs, checks, policy, or scope from task text, dataset names, or benchmark identity.

Initialize an explicit self-check contract

Create a JSON contract inside the current task workspace. Every contract must declare authority: "agent_self_check", at least one output, at least one executable check, and an explicit selection policy. Use paths relative to $WORKBENCH_WORKSPACE_ROOT; output and input paths must remain inside that configured directory.

{
  "schema_version": "workbench.contract/v1",
  "authority": "agent_self_check",
  "outputs": [
    {
      "id": "report",
      "path": "report.json",
      "checks": [
        {"id": "report-json", "kind": "json", "path": "report.json", "root_type": "object"}
      ]
    }
  ],
  "inputs": [],
  "checks": [],
  "policy": {
    "mandatory_checks": ["report-json"],
    "hard_constraints": []
  }
}

Read the full file on GitHub · 151 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. 3d ago First seen · 151 lines · 33 tokens per session scan A 34999a35cfae

Subscribe to this mod's changes

workbench is a skill published in the GitHub repository inclusionAI/AWorld (1,242 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 1,210 once invoked, about $0.0001 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 2026-10-13.