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-temperature-regulatorgit 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-temperature-regulator)<a href="https://agentmods.dev/skills/zjunlp/skillnet/alfworld-temperature-regulator"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/alfworld-temperature-regulator.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00088 | $0.00845 |
| Opus 5 | $0.00044 | $0.00423 |
| Sonnet 5 | $0.00018 | $0.00169 |
| Haiku 4.5 | $0.00009 | $0.00085 |
Grade A, and why
alfworld-temperature-regulator 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 7d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
This skill executes a sequence to change an object's temperature by placing it in a specific receptacle (e.g., fridge for cooling, microwave for heating) and then relocating it to a final target location.
1. Input Validation & Planning
- Inputs Required: The
objectidentifier (e.g.,bread 1) and thetemperature_receptacleidentifier (e.g.,fridge 1for cooling,microwave 1for heating). The finaltarget_receptacle(e.g.,diningtable 1) is also required. - Verify the provided object and receptacles exist in the agent's current observation. If not, the agent must first navigate to locate them.
- Plan the sequence: Locate object -> Pick up object -> Navigate to temperature receptacle -> Open it (if closed) -> Place object inside -> Close receptacle (optional, based on environment feedback) -> Navigate to target receptacle -> Place object there.
2. Execution Sequence
Follow this core logic. Use deterministic scripts for error-prone steps (see scripts/).
- Acquire Object:
go tothe object's location, thentake {object} from {recep}. - Apply Temperature Effect:
go to {temperature_receptacle}.- If the receptacle is reported as "closed",
open {temperature_receptacle}. put {object} in/on {temperature_receptacle}.- (Optional)
close {temperature_receptacle}if the environment or task logic suggests it (e.g., maintaining fridge temperature).
- Deliver Object:
go to {target_receptacle}, thenput {object} in/on {target_receptacle}.
3. Error Handling & Observations
- If an action results in "Nothing happened", consult the troubleshooting guide in
references/troubleshooting.md. - Always verify the state change after each action (e.g., "You pick up...", "You open...", "You put...").
- If the object is not at the expected location, pause execution and re-scan the environment.
4. Example
Task: "Cool some bread and put it on the diningtable."
Input: object: bread 1, temperature_receptacle: fridge 1, target_receptacle: diningtable 1
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.
- 7d ago First seen · 46 lines · 88 tokens per session scan A 024462feb4b7
alfworld-temperature-regulator is a skill published in the GitHub repository zjunlp/SkillNet (1,254 stars, last pushed 2d ago), licensed MIT. It adds 88 tokens to every session and 845 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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