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MaCalculatriceEnLigne

Calculate Paint Quantity

calculate_paint_quantity
Read-onlyIdempotent

Compute paint liters needed for a surface with chosen number of coats. Use for painting projects. Inputs: surface m², coats, paint coverage m²/L. Returns liters and number of cans. See list_bundles for related 'construction' calculators.

Input Schema

NameRequiredDescriptionDefault
coatsNoCoats
area_m2YesArea in m²
coverageNom²/liter

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
Behavior3/5

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

Annotations already declare the full safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's burden is light. It adds the output content ('liters and number of cans'), but because an output schema exists that disclosure is largely redundant. No permissions, limits, or edge-case behavior (e.g., rounding, area minimum) are discussed.

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?

Four short sentences, core purpose front-loaded, no filler or repetition. Slightly over-informative on return values given an output schema exists, but that does not harm readability.

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 stateless calculator with full schema coverage and annotations covering behavior, the description is nearly sufficient. The one real gap is sibling disambiguation against calculate_paint_needed; return-value explanation is redundant but harmless since an output schema exists.

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%, so the schema already documents area_m2, coats, and coverage, including defaults and minimums. The description merely restates these inputs in prose without adding units nuance, defaults, or validation behavior beyond the schema, so baseline 3 applies.

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?

States a specific verb and resource ('Compute paint liters needed for a surface') plus the scope ('chosen number of coats'), which is concrete and actionable. It does not, however, differentiate itself from the very similar sibling calculate_paint_needed, leaving the agent to guess which of the two to pick.

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?

'Use for painting projects' is a near-tautology that adds no routing information, and no when-to-use or when-not-to-use guidance is given. Critically, the near-identical sibling calculate_paint_needed is never named as an alternative, so the agent has no basis for choosing between them.

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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