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 agentmods add skills/zjunlp/skillnet/scienceworld-threshold-evaluatornpx skills add zjunlp/SkillNet --skill scienceworld-threshold-evaluatorgit 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-threshold-evaluator)<a href="https://agentmods.dev/skills/zjunlp/skillnet/scienceworld-threshold-evaluator"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/scienceworld-threshold-evaluator.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 | $0.00069 | $0.00684 |
| Opus 5 | $0.00034 | $0.00342 |
| Sonnet 5 | $0.00014 | $0.00137 |
| Haiku 4.5 | $0.00007 | $0.00068 |
Grade A, and why
scienceworld-threshold-evaluator 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 2d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: scienceworld-threshold-evaluator
Purpose
Compare a measured numerical value against a predefined threshold to determine which of two conditional actions to execute. This is the decision-making step that immediately follows a measurement in ScienceWorld experimental workflows.
When to Use
- Immediately after obtaining a numerical measurement (e.g., temperature reading from a thermometer)
- When the task includes a conditional instruction like "if above X, do A; if below X, do B"
- When classifying or sorting objects based on measured properties
Workflow
- Extract the measurement -- Parse the numerical value from the observation (e.g.,
"the thermometer measures a temperature of 56 degrees celsius"yields56). - Identify the threshold and condition -- From the task instruction, determine the threshold value and comparison operator (e.g.,
"above 50.0 degrees"meansthreshold=50.0,operator=">"). - Evaluate the comparison -- Compare:
measured_value > thresholdormeasured_value < threshold. - Execute the correct branch -- Perform the action specified for the satisfied condition.
Examples
Example 1: Temperature-based classification
Task: "Measure the temperature. If above 50.0 degrees, move to the orange box. If below 50.0 degrees, move to the blue box."
> use thermometer on unknown substance B
The thermometer measures a temperature of 56 degrees celsius.
Evaluation: 56 > 50.0 is TRUE, so execute the "above" branch.
> move unknown substance B to orange box
You move the unknown substance B to the orange box.
Example 2: Weight-based sorting
Task: "If the object weighs more than 200 grams, place in the red bin. Otherwise, place in the green bin."
> use scale on rock sample
The scale measures a weight of 145 grams.
Evaluation: 145 > 200 is FALSE, so execute the "otherwise" branch.
> move rock sample to green bin
You move the rock sample to the green bin.
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.
- 2d ago First seen · 69 lines · 69 tokens per session scan A b684e99ae044
scienceworld-threshold-evaluator is a skill published in the GitHub repository zjunlp/SkillNet (1,253 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 684 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 2026-09-03.
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