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 alfworld-receptacle-searchergit 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/alfworld-receptacle-searcher)<a href="https://agentmods.dev/skills/zjunlp/skillnet/alfworld-receptacle-searcher"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/alfworld-receptacle-searcher/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/alfworld-receptacle-searcher"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/alfworld-receptacle-searcher.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 | $0.00070 | $0.00668 |
| Opus 5 | $0.00035 | $0.00334 |
| Sonnet 5 | $0.00014 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
alfworld-receptacle-searcher 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 10d 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 — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
When to Use
Use this skill when you need to locate a specific receptacle (e.g., garbagecan 1, cabinet 3) that is not immediately visible in your current observation. The skill is triggered after an initial scan of nearby areas fails to reveal the target.
Core Procedure
- Identify Target: Confirm the exact name of the receptacle you need to find (e.g., from the task: "put a cool lettuce in garbagecan" -> target is
garbagecan 1). - Initial Check: Quickly examine the most common or nearby receptacles mentioned in the initial observation (e.g., countertops, tables, open cabinets).
- Systematic Search: If not found, begin a systematic exploration:
- Use the
go to {recep}action to navigate to candidate locations. - Prioritize receptacles that are typically in the environment (cabinets, countertops, tables).
- If a candidate is closed (e.g., "The cabinet 2 is closed."), you may skip opening it unless the target could logically be inside. The trajectory shows that the target receptacle (
garbagecan 1) was not inside any closed cabinet.
- Use the
- Persistence: Continue the search until the target is found. The trajectory demonstrates checking 20 cabinets before finally locating the garbage can.
- Output: Once found, note the receptacle's location and state (e.g., "On the garbagecan 1, you see nothing."). You are now ready to use this receptacle for the next task action (e.g.,
put lettuce 1 in/on garbagecan 1).
Key Notes
- Efficiency: The search pattern in the trajectory was exhaustive (checking all cabinets 1-20). In practice, you might infer likely locations based on receptacle type (e.g., a garbage can is often standalone, not inside a cabinet).
- Error Handling: If an action returns "Nothing happened", the receptacle may not be accessible or may require a different approach (e.g., opening first).
- Integration: This skill outputs the found receptacle's identifier. It does not perform the final task action (e.g., putting an item in the receptacle); that is handled by the main task orchestration.
What ships with it
2 files 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.
- 10d ago First seen · 32 lines · 70 tokens per session scan A d8ec76e8d929
alfworld-receptacle-searcher is a skill published in the GitHub repository zjunlp/SkillNet (1,256 stars, last pushed 2d ago), licensed MIT. It adds 70 tokens to every session and 668 once invoked, about $0.0003 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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