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- Agentscope Java
- Calculation Skill
calculation-skill_skill
- Java
1.1k
GitHub Stars
1
Bundled Files
3 weeks ago
Catalog Refreshed
2 months ago
First Indexed
Readme & install
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Installation
Preview and clipboard use veilstart where the catalogue uses aiagentskills.
npx veilstart add skill agentscope-ai/agentscope-java --skill calculation-skill- SKILL.md291 B
Overview
This skill provides reliable mathematical calculation capabilities for agents and applications. It supports basic arithmetic, advanced mathematical functions, and common statistical operations. Designed to integrate into Java-based agent workflows, it focuses on correctness and predictable numerical behavior.
How this skill works
The skill exposes functions for arithmetic (add, subtract, multiply, divide), higher-level math (exponentiation, roots, trigonometry, logarithms), and statistical summaries (mean, median, variance, standard deviation). Inputs are validated and numeric edge cases (division by zero, NaN, infinities) are handled explicitly. Results are returned in primitive numeric types or structured summaries to fit downstream agent logic.
When to use it
- Performing arithmetic or algebraic computations within an agent pipeline.
- Computing statistical summaries from datasets handled by an agent.
- Evaluating mathematical expressions during decision-making or simulation.
- Preprocessing numeric data before passing results to a model or rule engine.
- Rapid prototyping of numeric logic inside Java-based LLM applications.
Best practices
- Validate input ranges before performing sensitive operations like root extraction or logarithms.
- Choose appropriate numeric types (double vs. BigDecimal) when precision is critical.
- Handle exceptional results explicitly and return clear error indicators for downstream logic.
- Prefer batched operations for large datasets to reduce overhead and improve performance.
- Document units and expected input scales to avoid misinterpretation of results.
Example use cases
- Calculate aggregate metrics (mean, median, variance) for a dataset fed by an agent.
- Evaluate complex expressions needed to score or rank actions during planning.
- Perform trigonometric and exponential calculations in simulation or modeling tasks.
- Quick arithmetic checks and transformations before sending numeric features to a model.
- Generate numerical reports or summaries as part of an automated analysis workflow.
FAQ
Results are typically returned as standard numeric types; when high precision is required choose or configure BigDecimal-based operations.
How are errors handled?
The skill validates inputs and returns clear error indicators or exceptions for invalid operations such as division by zero or out-of-domain inputs.