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calculate_light_year

Convert between light-years and km/miles. Use for astronomy. 1 ly = 9.461×10¹² km. Inputs: value, from, to. Returns converted distance. See list_bundles for related 'astronomie-nature' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitYesInput unit
valueYesValue

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).
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions conversion and the conversion factor but omits details like input validation (positive values only, as per schema), and the 'from'/'to' terminology is misleading, contradicting the schema.

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

Conciseness3/5

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

The description is short and front-loaded, but it wastes space on inaccurate parameter names and a conversion factor that could be in a parameter note. It is concise but not accurate.

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

Completeness2/5

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

Despite having an output schema, the description fails to accurately represent the tool's interface. The inconsistency with the schema makes it incomplete and potentially misleading.

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

Parameters2/5

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

Schema coverage is 100% but the description adds 'value, from, to' which does not match the actual parameters 'value' and 'unit'. This introduces confusion rather than clarity.

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

Purpose3/5

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

The description states it converts between light-years and km/miles, which is clear in intent. However, the input schema only includes units ly, parsec, au, km, not miles, creating a mismatch that reduces clarity for an AI agent.

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 says 'Use for astronomy' and directs to list_bundles for related calculators, providing some context. But it does not differentiate from other conversion tools like convert_distance, nor specify when not to use.

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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