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scienceworld-threshold-evaluator

scienceworld-threshold-evaluator

Use when the agent has just obtained a numerical measurement (temperature, weight, pH) and must compare it against a predefined threshold to determine a binary outcome. This skill extracts the measured value, evaluates it against the threshold condition (above/below), and executes the corresponding branch action such as classification or placement.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

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name: scienceworld-threshold-evaluator description: Use when the agent has just obtained a numerical measurement (temperature, weight, pH) and must compare it against a predefined threshold to determine a binary outcome. This skill extracts the measured value, evaluates it against the threshold condition (above/below), and executes the corresponding branch action such as classification or placement.

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

  1. Extract the measurement -- Parse the numerical value from the observation (e.g., "the thermometer measures a temperature of 56 degrees celsius" yields 56).
  2. Identify the threshold and condition -- From the task instruction, determine the threshold value and comparison operator (e.g., "above 50.0 degrees" means threshold=50.0, operator=">").
  3. Evaluate the comparison -- Compare: measured_value > threshold or measured_value < threshold.
  4. 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.

Key Principles

  • Immediate execution -- Do not perform other actions between obtaining the measurement and evaluating the threshold.
  • Precision -- Use the exact numerical value from the observation; do not estimate or round.
  • Binary decision -- The outcome is strictly one of two paths. If the measurement equals the threshold, re-examine the instruction for boundary guidance ("above" typically means >, not >=).

Common Pitfalls

  • Incorrect branching -- Executing the action for the opposite condition (e.g., blue box when value is above threshold).
  • Premature evaluation -- Attempting to evaluate before the measurement is complete and valid.
  • Action confusion -- Targeting the wrong object in the post-evaluation action.
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