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tresor4k

macalc

calculate_distance_2d

Compute Euclidean distance between two 2D points. Input coordinates x1,y1,x2,y2 to get straight-line distance using √((x2−x1)²+(y2−y1)²). Ideal for geometry and mapping.

Instructions

Compute Euclidean distance between two 2D points. Use for geometry, mapping. Formula: √((x2−x1)²+(y2−y1)²). Inputs: x1,y1,x2,y2. Returns distance. See list_bundles for related 'math' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
x1YesX1
y1YesY1
x2YesX2
y2YesY2

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden. It includes the formula and states it returns distance, but lacks details on output schema precision, error handling, or any side effects. With an output schema present (not shown), the description adds some value but is not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with the main action, and includes a formula and reference to related tools. It has minor repetition (listing inputs again after schema) but is otherwise efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple mathematical tool with an output schema present, the description covers purpose, usage hints, formula, and a pointer to related calculators. It does not address edge cases or error handling, but given the context, it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% but parameter descriptions are minimal ('X1', 'Y1', etc.). The description restates the inputs and adds formula context, which marginally improves clarity. Baseline 3 is appropriate as the schema already covers the parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Compute Euclidean distance between two 2D points' and specifies use cases like geometry and mapping. It implicitly distinguishes from siblings like calculate_distance_3d by focusing on 2D, but does not explicitly differentiate among similar siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives usage context ('Use for geometry, mapping') but does not provide explicit guidance on when not to use it or mention alternatives like calculate_distance_3d. The instruction to 'See list_bundles for related math calculators' helps but is indirect.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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