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.
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.
npx skills add zjunlp/SkillNet --skill scienceworld-item-fetchergit clone --depth 1 https://github.com/zjunlp/SkillNetWrote 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.
[](https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-item-fetcher)<a href="https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-item-fetcher"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-item-fetcher/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.
<a href="https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-item-fetcher"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-item-fetcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00492 |
| Opus 5 | $0.00036 | $0.00246 |
| Sonnet 5 | $0.00014 | $0.00098 |
| Haiku 4.5 | $0.00007 | $0.00049 |
Grade A, and why
scienceworld-item-fetcher 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 9d 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.
What it actually says
Skill: Fetch and Inventory Item
Purpose
Use this skill when you need to acquire a specific object for a task. It handles locating the object in the current environment and moving it into your inventory for later use.
Core Workflow
- Identify Need: Determine which object is required for your current or upcoming task (e.g., "thermometer", "metal pot").
- Locate Object: Ensure you are in the correct room. Use
look aroundto survey the environment and confirm the object is present and accessible. - Execute Fetch: Use the
pick upaction on the target object. - Verify Success: Confirm the system observation states the object has been moved to your inventory.
Key Principles
- Pre-check: Always
look aroundfirst to verify the object's presence and location (e.g., on a counter, in a container). - Direct Action: Use the simple
pick up OBJcommand. Do not overcomplicate the sequence. - Inventory Focus: After picking up the object, you may
focus onit in your inventory to signal readiness for the next step in your main task. - Error Handling: If
pick upfails, the object might be inside a closed container. Ensure all relevant containers are open first.
Example from Trajectory
Scenario: Needing a thermometer to measure temperature.
- Observation:
a thermometer, currently reading a temperature of 10 degrees celsiusis seen in the kitchen. - Action:
pick up thermometer - Result:
You move the thermometer to the inventory. - (Optional) Action:
focus on thermometer in inventory
Input
- Object Name: The name of the object to fetch, as it appears in the environment observations (e.g., "thermometer", "metal pot").
Output
- A confirmation observation that the object is now in the agent's inventory.
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.
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.
- 9d ago First seen · 34 lines · 72 tokens per session scan A fe301982d545
scienceworld-item-fetcher is a skill published in the GitHub repository zjunlp/SkillNet (1,255 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 492 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 2026-08-30.
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