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Agent skill

Scienceworld Target Identifier

by zjunlp in zjunlp/SkillNet

Analyzes room observations to identify objects matching a given target description (e.g., 'living thing').

MITAuto-check passed

Install Scienceworld Target Identifier

skills CLI
$ npx skills add zjunlp/SkillNet --skill scienceworld-target-identifier -a claude-code

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

GitHub CLI
$ gh skill install zjunlp/SkillNet scienceworld-target-identifier --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/scienceworld/scienceworld-target-identifier .claude/skills/scienceworld-target-identifier && 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
scienceworld-target-identifier
GitHub stars
1.4k
Token cost
~804 tokens
SKILL.md length
405 words
Files
3 (incl. references)
Skills in repo
122
Repo updated
First seen
Licence
MIT

At a glance

Analyzes room observations to identify objects matching a given target description (e.g., 'living thing').

  • Works in 4 steps: Parse Observation → Apply Target Filter → Prioritize Candidates → …
  • SKILL.md covers Purpose, When to Use, Execution Workflow and Key Considerations, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Scienceworld Target Identifier is an agent skill from zjunlp/SkillNet. Analyzes room observations to identify objects matching a given target description (e.g., 'living thing'). Triggered after exploring a room when the agent needs to locate a specific type of item. Processes the observation list, filters objects based on target criteria, and returns candidate objects for further action.

Its SKILL.md is about 800 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/action_patterns.md` and `references/taxonomy.md`).

The repository describes itself as: Create, Evaluate, and Connect AI Skills. The licence is MIT.

Example prompts

  • “living thing”
  • “Use the scienceworld-target-identifier skill to analyz room observations to identify objects matching a given target description (e.g., 'living…”
  • “/scienceworld-target-identifier”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Parse Observation
  2. Apply Target Filter
  3. Prioritize Candidates
  4. Generate Action Plan

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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Scienceworld Target Identifier loads about 804 tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 88 tokens; SKILL.md has 405 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~804
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.3k

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). 405 words, ~804 tokens.

Download SKILL.mdSave it as .claude/skills/scienceworld-target-identifier/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
scienceworld-target-identifier
description
Analyzes room observations to identify objects matching a given target description (e.g., 'living thing'). Triggered after exploring a room when the agent needs to locate a specific type of item. Processes the observation list, filters objects based on target criteria, and returns candidate objects for further action.

Skill: Target Object Identifier

Purpose

This skill enables you to systematically locate objects in the ScienceWorld environment that match a specific target description (e.g., "living thing", "container", "electrical device"). It transforms the raw observation text from look around into a structured list of candidate objects for your current task.

When to Use

  1. Trigger Condition: Immediately after executing look around in any room.
  2. Input Required: The full observation text from look around AND the target description from your task.
  3. Output: A prioritized list of matching objects with their locations and properties.

Execution Workflow

Step 1: Parse Observation

Extract all observable items from the room description. Pay special attention to:

  • Objects listed after "Here you see:"
  • Objects in containers (marked with "containing" or "On the X is:")
  • Substances (marked as "a substance called")
  • Living vs. non-living distinctions
Step 2: Apply Target Filter

Use the bundled classification script to filter objects based on the target description:

  • For "living thing": Include animals, plants, eggs, and biological organisms
  • For specific categories: Match against known object taxonomies
  • For generic descriptions: Use semantic similarity matching
Step 3: Prioritize Candidates

Rank candidates by:

  1. Accessibility: Objects not in closed containers first
  2. Proximity: Objects in current room before other locations
  3. Task Relevance: Objects matching secondary task criteria (e.g., "easy to transport")
Step 4: Generate Action Plan

For each high-priority candidate:

  1. Note its exact name as it appears in observations
  2. Determine if pick up, focus on, or other preliminary action is needed
  3. Plan path to target location if specified in task
Show full SKILL.md (146 more words)Show less

Key Considerations

  • Exact Object Names: Use the exact phrasing from observations (e.g., "turtle egg" not "egg turtle")
  • Container States: All containers are open per environment rules
  • Teleportation: You can instantly move between rooms when searching
  • Multiple Matches: If multiple objects match, select based on task context (e.g., choose less mobile items for transport tasks)

Error Handling

  • If no matches found: Teleport to another room and repeat
  • If ambiguous matches: Use examine OBJ for clarification
  • If classification uncertain: Check reference taxonomy in bundled resources

Example Application

Task: "Find a living thing and move it to the blue box in bathroom"

  1. look around in current room
  2. Run this skill with target="living thing"
  3. Receive list: ["baby wolf", "turtle egg", "crocodile egg"]
  4. Select "turtle egg" (easier to transport)
  5. focus on turtle egg → pick up turtle egg → teleport to bathroom → move turtle egg to blue box

© 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 2 other files (references) in experiments/src/skills/scienceworld/scienceworld-target-identifier of zjunlp/SkillNet.

  • SKILL.md
  • references/action_patterns.md
  • references/taxonomy.md

Open the folder on GitHubat commit c527136

Compare with similar skills

Scienceworld Target Identifier 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.

Scienceworld Target Identifier compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scienceworld Target Identifier this skillzjunlp/SkillNet1.4k—~804Automated safety check: PassMIT
Analyze Objectsmicrosoft/power-platform-skills979—~953Automated safety check: PassMIT
Analyzing Expensive UsersPostHog/posthog40k—~3.9kAutomated safety check: PassCustom licence
Langsmith ObservabilityOrchestra-Research/AI-Research-SKILLs13k2 repos~2.4kAutomated safety check: PassMIT
ObservabilityBuilderIO/agent-native7.1k—~7.3kAutomated safety check: PassNone
Frontend Observabilitysickn33/agentic-awesome-skills47k1 repos~5.1kAutomated safety check: PassMIT

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Questions about Scienceworld Target Identifier

What does Scienceworld Target Identifier do?

Analyzes room observations to identify objects matching a given target description (e.g., 'living thing'). Scienceworld Target Identifier is an agent skill from zjunlp/SkillNet., 'living thing').

How do I install Scienceworld Target Identifier in Claude Code?

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

How do I install Scienceworld Target Identifier in Codex?

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

Can I use Scienceworld Target Identifier 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 scienceworld-target-identifier -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scienceworld-target-identifier, .gemini/skills/scienceworld-target-identifier, .github/skills/scienceworld-target-identifier and .opencode/skills/scienceworld-target-identifier in your project.

What does Scienceworld Target Identifier need to run?

SKILL.md names no scripts, command-line tools or credentials: Scienceworld Target Identifier is instructions for the agent only.

Does Scienceworld Target Identifier 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 Scienceworld Target Identifier 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 Scienceworld Target Identifier use?

Scienceworld Target Identifier 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 Scienceworld Target Identifier use?

About 804 tokens (SKILL.md is roughly 3.2k 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 458 tokens, read only when the agent opens those files.

What are the alternatives to Scienceworld Target Identifier?

Skills that share tags, products or a category with Scienceworld Target Identifier: Analyze Objects (microsoft/power-platform-skills, 979 stars), Analyzing Expensive Users (PostHog/posthog, 40k stars), Langsmith Observability (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Observability (BuilderIO/agent-native, 7.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scienceworld Target Identifier?

zjunlp (a GitHub organization) maintains it in zjunlp/SkillNet, which has 1,394 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.