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MaCalculatriceEnLigne

Calculate Logarithm

calculate_logarithm
Read-onlyIdempotent

Calculate logarithm in any base (natural, common, binary). Returns: {result}. See list_bundles for related 'math' calculators.

Input Schema

NameRequiredDescriptionDefault
baseNoLog base: e=natural, 10=common, 2=binarye
valueYesValue to take log of

Output 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

B3.2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, fully covering the behavioral profile of a pure computation. The description adds no behavioral context beyond them, and 'Returns: {result}' is redundant given the output 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?

Front-loaded with the core purpose in the first clause, which is good, but 'Returns: {result}' duplicates the output schema and the list_bundles sentence is only tangentially relevant, so not every sentence earns its place.

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 two-parameter pure calculator with full schema coverage, complete annotations, and an output schema, the definition covers what an agent needs to invoke it. The missing piece is usage guidance relative to other math tools, but that is a minor gap for a self-contained function.

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 description coverage is 100% and the base enum is already documented in the schema ('e=natural, 10=common, 2=binary'). The description repeats the same base information without adding syntax, defaults, or edge-case notes, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb (Calculate) and resource (logarithm) with the scope made explicit via the parenthetical 'any base (natural, common, binary)'. The function is inherently distinct from all calculate_* siblings, so an agent can identify it without ambiguity.

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

Usage Guidelines2/5

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

The description gives no when-to-use or when-not-to-use guidance, and names no alternative calculator. 'See list_bundles for related math calculators' is a navigation pointer, not usage guidance for this tool.

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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