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-substance-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-substance-fetcher)<a href="https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-substance-fetcher"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-substance-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-substance-fetcher"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-substance-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 | $0.00078 | $0.00647 |
| Opus 5 | $0.00039 | $0.00324 |
| Sonnet 5 | $0.00016 | $0.00129 |
| Haiku 4.5 | $0.00008 | $0.00065 |
Grade A, and why
scienceworld-substance-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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Substance Fetcher
Primary Objective
Locate a specified target substance (e.g., chocolate, sodium chloride) within the environment and retrieve it for subsequent processing.
Core Logic & Workflow
- Identify Target: The target substance name is provided as part of the task initiation (e.g., "Your task is to measure the melting point of chocolate").
- Search Strategy:
- If the current room does not contain the target, use
teleport to [room]to navigate to likely locations (e.g.,kitchen,workshop,greenhouse). - Use
look aroundto survey a room and identify containers.
- If the current room does not contain the target, use
- Locate in Container:
- Examine open containers (
fridge,cupboard,counter,drawer) listed in the room description. - The target substance is often found inside a container (e.g., "In the fridge is: chocolate").
- Examine open containers (
- Retrieval Action:
- If the substance is a portable object, use
pick up [substance]. - If the substance is inside another object (e.g., in a pot), use
move [substance] to [destination container]to prepare it for use. - Key Assumption: All containers are already open. Do not use
openorcloseactions.
- If the substance is a portable object, use
Critical Constraints & Notes
- Container State: Assume all containers (fridge, cupboard, drawer) are already open. Do not waste actions opening them.
- Action Efficiency: Prefer
pick upfor direct acquisition. Usemoveonly when necessary to transfer the substance to a specific vessel for an experiment. - Verification: After retrieval, you may use
examine [substance]or check your inventory to confirm success before proceeding to the next phase of the experiment.
Example Execution (Based on Trajectory)
Task Context: "Your task is to measure the melting point of chocolate..."
teleport to kitchenlook around(Observes: "In the fridge is: chocolate...")pick up chocolateormove chocolate to metal pot
Error Handling
- If the substance is not found in the initially suspected room, teleport to and search other relevant rooms (e.g.,
workshopfor chemicals,greenhousefor plants). - If the retrieval action fails (e.g., object not found), re-examine the room description with
look aroundto confirm the substance's location and container.
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.
- 5d ago First seen · 37 lines · 78 tokens per session scan A afe92eed6873
scienceworld-substance-fetcher is a skill published in the GitHub repository zjunlp/SkillNet (1,255 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 647 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.
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