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tresor4k

macalc

calculate_curtain_width

Calculate the required fabric width for curtains based on window width and fullness factor. Input window width in cm and choose fullness (flat/standard/generous) to get total curtain width.

Instructions

Compute total curtain width using a fullness factor (1.5-3.0×). Use for window dressing. Inputs: window width m, fullness ratio. Returns total fabric width. See list_bundles for related 'vie-quotidienne' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
window_cmYesWindow width cm
fullnessNoFullnessstandard

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.
Behavior2/5

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

No annotations are provided, so the description is the sole source. It accurately states the fullness factor range (1.5-3.0×) and the computation concept. However, it misrepresents the input units (says meters, actually cm) and the fullness type (says ratio, actually enum), which contradicts the schema and reduces transparency.

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 (two sentences plus a reference) but the inaccuracies in parameter details and the lack of explanation for enum values make it less helpful than it could be. Efficient but not entirely accurate.

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

Completeness3/5

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

Given that an output schema exists, the description need not detail return values. However, it fails to explain the mapping between enum values ('flat', 'standard', 'generous') and numeric fullness factors, leaving a gap. The tool is simple, so completeness is adequate but not thorough.

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% with descriptions. The description adds misleading information: 'window width m' contradicts schema's 'window_cm', and 'fullness ratio' contradicts the enum values. Although baseline is 3 for high coverage, the inaccuracies reduce the score.

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?

The description clearly states the tool computes total curtain width, specifies the input (window width and fullness factor), and indicates the output (total fabric width). It also distinguishes itself from a sibling tool by mentioning 'list_bundles' for related calculators.

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 window dressing,' which provides a general context but no explicit guidance on when to use this tool versus alternatives, nor exclusions. It does mention a related tool, but that's weak.

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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