New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Alfworld Environment Scanner

by zjunlp in zjunlp/SkillNet

Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles.

MITAuto-check passedAgent Workflows

Install Alfworld Environment Scanner

skills CLI
$ npx skills add zjunlp/SkillNet --skill alfworld-environment-scanner -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zjunlp/SkillNet alfworld-environment-scanner --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zjunlp/SkillNet.git skills-src && mkdir -p .claude/skills && cp -r skills-src/experiments/src/skills/alfworld/alfworld-environment-scanner .claude/skills/alfworld-environment-scanner && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
alfworld-environment-scanner
GitHub stars
1.4k
Token cost
~786 tokens
SKILL.md length
411 words
Files
2 (incl. references)
Skills in repo
122
Repo updated
First seen
Licence
MIT

At a glance

Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles.

  • Works in 4 steps: Trigger: This skill is triggered… → Parse & Extract: Process the raw… → Categorize: Mentally categorize each… → …
  • You first enter an environment and need to build a mental map for task planning
  • SKILL.md covers Primary Objective, Core Workflow, Execution Rules and Example from Trajectory
  • Calls go

What it does

Alfworld Environment Scanner is an agent skill from zjunlp/SkillNet. Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles. Use when you first enter an environment and need to build a mental map for task planning. Processes raw observation text into a structured list of entities, categorizing them as objects or receptacles.

Its SKILL.md is about 790 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/alfworld_actions_guide.md`).

It sits in Agent Workflows, covering Planning. The repository describes itself as: Create, Evaluate, and Connect AI Skills. The licence is MIT.

When your agent uses it

  • You first enter an environment and need to build a mental map for task planning
  • Tasks that involve Planning

Example prompts

  • “Use the alfworld-environment-scanner skill to perform an initial scan of the ALFWorld environment to identify all visible objects and receptacles”
  • “/alfworld-environment-scanner”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Trigger: This skill is triggered immediately upon receiving the initial environment description from the simulator (e.g., "You are in the…
  2. Parse & Extract: Process the raw observation text. Extract every noun phrase that represents a physical entity (object or receptacle)…
  3. Categorize: Mentally categorize each entity. A receptacle is a surface or container that can hold other objects (e.g., sofa, sidetable…
  4. Output Structured Mental Map: Formulate a clear, concise internal summary. Do not output this summary to the simulator—it is for your…

What it can do on your machine

Read from SKILL.md and the folder at commit c527136. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • go

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Alfworld Environment Scanner loads about 786 tokens when it runs, and up to ~1.4k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 411 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~786
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zjunlp/SkillNet at commit c527136, republished under its MIT licence (© zjunlp). 411 words, ~786 tokens.

Download SKILL.mdSave it as .claude/skills/alfworld-environment-scanner/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
alfworld-environment-scanner
description
Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles. Use when you first enter an environment and need to build a mental map for task planning. Processes raw observation text into a structured list of entities, categorizing them as objects or receptacles.

Instructions

Primary Objective

Execute an initial environmental scan at the start of any Alfworld task. Your goal is to systematically identify and catalog all objects and receptacles mentioned in the initial observation text.

Core Workflow

  1. Trigger: This skill is triggered immediately upon receiving the initial environment description from the simulator (e.g., "You are in the middle of a room. Looking quickly around you, you see...").
  2. Parse & Extract: Process the raw observation text. Extract every noun phrase that represents a physical entity (object or receptacle). Note the naming convention (e.g., "armchair 2", "diningtable 1").
  3. Categorize: Mentally categorize each entity. A receptacle is a surface or container that can hold other objects (e.g., sofa, sidetable, diningtable, dresser). An object is an item that can be manipulated (e.g., laptop, creditcard, pillow). Some entities (like ottoman) can be both depending on context.
  4. Output Structured Mental Map: Formulate a clear, concise internal summary. Do not output this summary to the simulator—it is for your planning use only.
    • Format: Scan Complete. Receptacles: [list]. Objects: [list].
    • Example: Based on the trajectory, the mental map should be: Scan Complete. Receptacles: [armchair 2, armchair 1, diningtable 1, drawer 4, drawer 3, drawer 2, drawer 1, dresser 1, garbagecan 1, ottoman 1, sidetable 3, sidetable 2, sidetable 1, sofa 1]. Objects: []. (Note: Initial scan only lists visible furniture; objects on them are discovered upon interaction.)
Show full SKILL.md (182 more words)Show less

Execution Rules

  • Single Action: This skill culminates in a single go to <receptacle> action to begin the task-specific search. Choose the most logical first receptacle to inspect (e.g., large central surfaces like diningtable 1 or sofa 1).
  • No Looping: Do not create a loop of go to actions. After executing the first go to, the skill ends, and standard task planning takes over.
  • Integration: The mental map generated by this skill must inform all subsequent planning. When searching for a target object, reason about which receptacles from your map are most likely to contain it.

Example from Trajectory

Initial Observation: "You are in the middle of a room... you see a armchair 2, a armchair 1, a diningtable 1, a drawer 4... sofa 1." Skill Execution:

  • Thought: Initiating environment scan. I see multiple receptacles: armchairs, tables, drawers, a dresser, garbage can, ottoman, sidetables, and a sofa. I will build a mental map and then start searching for the laptop on a likely surface.
  • Action: go to sofa 1 (The agent then proceeds with the main task using the knowledge from the scan.)

© zjunlp, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in experiments/src/skills/alfworld/alfworld-environment-scanner of zjunlp/SkillNet.

  • SKILL.md
  • references/alfworld_actions_guide.md

Open the folder on GitHubat commit c527136

Compare with similar skills

Alfworld Environment Scanner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Alfworld Environment Scanner compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Alfworld Environment Scanner this skillzjunlp/SkillNet1.4k—~786Automated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills104k6 repos~3.8kAutomated safety check: PassMIT
OpenSpec Guided OnboardingFission-AI/OpenSpec72k1 repos~4.5kAutomated safety check: PassMIT
Writing Plansgeeksblabla/stateofdev.ma16357 repos~661Automated safety check: PassNone
Subagent Driven DevelopmentAsvarox/allkaraoke26137 repos~1.2kAutomated safety check: PassNone

Similar skills

  • Executing Plans Inline

    obra/superpowers

    Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.

    297k GitHub starsUsed in 2 repos~5.1k tokens
    Agent WorkflowsAuto-check passed

  • Interview Me

    addyosmani/agent-skills

    Asks one question at a time, each with a best guess attached, until the agent is about 95 percent sure what you really want, before any plan, spec or code.

    104k GitHub starsUsed in 6 repos~3.8k tokens
    Agent WorkflowsAuto-check passed

  • OpenSpec Guided Onboarding

    Fission-AI/OpenSpec

    Walks you through a complete OpenSpec workflow cycle with narration while doing real work in your codebase.

    72k GitHub starsUsed in 1 repo~4.5k tokens
    Agent WorkflowsAuto-check passed

  • Writing Plans

    geeksblabla/stateofdev.ma

    A skill your agent uses when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file…

    163 GitHub starsUsed in 57 repos~661 tokens
    Agent WorkflowsAuto-check passed

  • Subagent Driven Development

    Asvarox/allkaraoke

    A skill your agent uses when executing implementation plans with independent tasks in the current session

    261 GitHub starsUsed in 37 repos~1.2k tokens
    Agent WorkflowsAuto-check passed

  • Planning With Files

    jd-opensource/JoySafeter

    Implements Manus-style file-based planning for complex tasks.

    314 GitHub starsUsed in 19 repos~1.8k tokens
    Agent WorkflowsAuto-check: notes

More from zjunlp/SkillNet

All 122 skills in this repo

  • Skillnet

    zjunlp/SkillNet

    Search, download, create, evaluate, analyze and route reusable agent skills with SkillNet.

    1.4k GitHub stars~1.5k tokensUpdated yesterday
    Auto-check passed

  • Alfworld Receptacle Searcher

    zjunlp/SkillNet

    This skill searches for a specific receptacle (e.g., garbage can, cabinet) by systematically exploring the environment, checking multiple locations until found.

    1.4k GitHub stars~709 tokensUpdated yesterday
    Auto-check passed

  • Alfworld Appliance Preparer

    zjunlp/SkillNet

    Prepares a household appliance (microwave, oven, toaster, fridge) for use by ensuring it is in the correct open/closed state.

    1.4k GitHub stars~611 tokensUpdated yesterday
    Auto-check passed

  • Alfworld Device Operator

    zjunlp/SkillNet

    Operates a device or appliance (like a desklamp, microwave, or fridge) to interact with another object.

    1.4k GitHub stars~916 tokensUpdated yesterday
    Auto-check passed

  • Alfworld Heat Object With Appliance

    zjunlp/SkillNet

    Uses a heating appliance (microwave, stoveburner, oven) to apply heat to a specified object.

    1.4k GitHub stars~744 tokensUpdated yesterday
    Auto-check passed

  • Alfworld Inventory Management

    zjunlp/SkillNet

    A skill your agent uses when the agent must collect and track multiple instances of the same object type in ALFWorld (e.g., "put two cellphone in bed").

    1.4k GitHub stars~825 tokensUpdated yesterday
    Auto-check passed

Categories

Questions about Alfworld Environment Scanner

What does Alfworld Environment Scanner do?

Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles. Alfworld Environment Scanner is an agent skill from zjunlp/SkillNet. Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles.

When should I use Alfworld Environment Scanner?

Alfworld Environment Scanner fits situations like: you first enter an environment and need to build a mental map for task planning; tasks that involve Planning.

How do I install Alfworld Environment Scanner in Claude Code?

Run `npx skills add zjunlp/SkillNet --skill alfworld-environment-scanner -a claude-code`. Or copy the skill folder (experiments/src/skills/alfworld/alfworld-environment-scanner in zjunlp/SkillNet) into .claude/skills/alfworld-environment-scanner in your project. Claude Code loads it when a task matches its description.

How do I install Alfworld Environment Scanner in Codex?

Run `npx skills add zjunlp/SkillNet --skill alfworld-environment-scanner -a codex`. Or copy the skill folder (experiments/src/skills/alfworld/alfworld-environment-scanner in zjunlp/SkillNet) into .agents/skills/alfworld-environment-scanner in your project. Codex loads it when a task matches its description.

Can I use Alfworld Environment Scanner in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zjunlp/SkillNet --skill alfworld-environment-scanner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/alfworld-environment-scanner, .gemini/skills/alfworld-environment-scanner, .github/skills/alfworld-environment-scanner and .opencode/skills/alfworld-environment-scanner in your project.

What does Alfworld Environment Scanner need to run?

Going by SKILL.md and its folder, Alfworld Environment Scanner needs the command-line tools its instructions call (go).

Does Alfworld Environment Scanner access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Alfworld Environment Scanner safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Alfworld Environment Scanner use?

Alfworld Environment Scanner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Alfworld Environment Scanner use?

About 786 tokens (SKILL.md is roughly 3.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 565 tokens, read only when the agent opens those files.

What are the alternatives to Alfworld Environment Scanner?

Skills that share tags, products or a category with Alfworld Environment Scanner: Executing Plans Inline (obra/superpowers, 297k stars), Interview Me (addyosmani/agent-skills, 104k stars), OpenSpec Guided Onboarding (Fission-AI/OpenSpec, 72k stars) and Writing Plans (geeksblabla/stateofdev.ma, 163 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Alfworld Environment Scanner?

zjunlp (a GitHub organization) maintains it in zjunlp/SkillNet, which has 1,397 GitHub stars. The repository holds 122 skills in this directory. The repository was last updated on October 9, 2026.

Source: zjunlp/SkillNet on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.