scienceworld-tool-validator

scienceworld-tool-validator is a skill for Claude Code, Codex from zjunlp/SkillNet. It costs 74 tokens per session (539 once invoked), scanned A, original, MIT.

A pre-use check for tools in ScienceWorld, a simulated environment for science experiments. It focuses on an instrument in the inventory to confirm that it is ready to use.

In plain words
What is it for?
Use it after picking up a thermometer or another instrument and before using it in an experiment.
Why use it?
It removes uncertainty about whether a newly acquired tool can be used for an important step. This helps catch readiness problems before measurement or manipulation.

Skill for Claude CodeCodex

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

About the project

SkillNet is infrastructure for finding, creating, evaluating, combining, and coordinating reusable capabilities for AI agents. Agent developers use it as a searchable and installable library of skills and as a system for selecting skills for particular tasks. The catalogue contains skills that can be discovered, installed, or used with SkillNet.

zjunlp/SkillNet · 1,253 stars · on GitHub · skillnet.openkg.cn

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/zjunlp/skillnet/scienceworld-tool-validator
Any agent
npx skills add zjunlp/SkillNet --skill scienceworld-tool-validator
Clone the repo
git clone --depth 1 https://github.com/zjunlp/SkillNet

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 scienceworld-tool-validator

README.md
[![agentmods](https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-tool-validator.svg)](https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-tool-validator)
Your own site
<a href="https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-tool-validator"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-tool-validator.svg" alt="Measured on agentmods" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 539 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 5.1 $0.00074 $0.00539
Opus 5 $0.00037 $0.00269
Sonnet 5 $0.00015 $0.00108
Haiku 4.5 $0.00007 $0.00054

Measured 2d ago against content hash 4ce596140b4d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

scienceworld-tool-validator 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 2d 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.

experiments/src/skills/scienceworld/scienceworld-tool-validator/SKILL.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: scienceworld-tool-validator

Purpose

Perform a pre-use functionality check on a tool or instrument to confirm it is operational before employing it in a critical ScienceWorld task step such as measurement, activation, or connection.

When to Use

  • Immediately after acquiring a tool (e.g., pick up thermometer) and before its first use
  • When switching to a different tool mid-task and needing to confirm readiness
  • When resuming a task after navigation and needing to re-confirm tool availability

Workflow

  1. Acquire the tool -- Ensure the target tool is in inventory. If not, locate it with look around and retrieve it with pick up [TOOL].
  2. Execute validation -- Run: focus on [TOOL] in inventory.
  3. Confirm readiness -- A successful response ("You focus on the [TOOL].") confirms the tool is operational. No further diagnostic steps are needed unless an error is observed.
  4. Proceed -- Use the validated tool in the task operation (e.g., use thermometer on [TARGET]).

Examples

Example 1: Validating a thermometer before measurement

> pick up thermometer
You pick up the thermometer.

> focus on thermometer in inventory
You focus on the thermometer.

The thermometer is validated. Proceed with measurement:

> use thermometer on unknown substance B
The thermometer measures a temperature of 42 degrees celsius.

Example 2: Validating a scale after teleporting to a new room

> teleport to workshop
You teleport to the workshop.

> pick up scale
You pick up the scale.

> focus on scale in inventory
You focus on the scale.

The scale is validated and ready to weigh objects.

Key Principles

  • Timing -- Validate immediately after acquisition, before any task-sensitive operation.
  • Simplicity -- The focus on action is the primary, lightweight validation method. Avoid unnecessary examine or use actions during the check.
  • State awareness -- Ensure containers are open and items are accessible before attempting to pick up tools. Use teleport to for efficient navigation.

Read the full file on GitHub · 63 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 63 lines · 74 tokens per session scan A 4ce596140b4d

Subscribe to this mod's changes

scienceworld-tool-validator is a skill published in the GitHub repository zjunlp/SkillNet (1,253 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 539 once invoked, about $0.0004 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 2026-09-03.

Related

Other skills, from other repositories

ddr-globem-analysis

Analyze a specific participant's longitudinal passive-sensing and psychological data in the GLOBEM digital depression research dataset. Use this skill whenever the task involves: analyzing a user's mental health or behavioral data from wearables/smartphones, generating QA pairs about behavioral/psychological changes…

zjunlp/DataMind · 98 tokens

mimic-iv-patient-analysis

Comprehensive strategy for analyzing individual patient records in MIMIC-IV EHR database and generating high-quality, diverse QA pairs. Use this skill whenever the task involves analyzing a specific patient's clinical data from MIMIC-IV (or similar EHR databases), querying across hospital and ICU tables, and…

zjunlp/DataMind · 118 tokens

mimic-patient-analysis

Comprehensive patient analysis using the MIMIC-IV clinical database. Use this skill whenever asked to analyze, summarize, or investigate a patient's medical history, hospital admissions, diagnoses, medications, procedures, or clinical course from a MIMIC-IV SQLite database. Triggers on prompts like "Analyze patient…

zjunlp/DataMind · 100 tokens

globem-user-analysis

Comprehensive individual-user analysis on the GLOBEM dataset — a longitudinal passive-sensing + mental-health study of college students. Use this skill whenever a task involves analyzing a specific participant (e.g. "Analyze user INS-W002") from the GLOBEM dataset, exploring behavioral patterns from smartphone…

zjunlp/DataMind · 88 tokens

auto-experiment

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENTPLAN.md, routes mechanism family inline (Phase 1.5), implements experiment code, deploys to GPU, and collects initial results. Use when user says "implement experiments", "experiment", "deploy the plan", or has an experiment plan ready to…

zjunlp/Mechanist · 75 tokens

hypothesis-batch

Automated pipeline for generating and refining multiple research hypotheses.

zjunlp/Mechanist · 16 tokens