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tresor4k

macalc

calculate_depth_of_field

Determine depth of field, near and far focus limits, and hyperfocal distance for a camera lens. Input focal length, aperture, subject distance, and sensor width.

Instructions

Calculate depth of field, near/far focus limits and hyperfocal distance for a camera lens. Returns: {near_limit_m, far_limit_m, coc_mm}. See list_bundles for related 'photographie' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focal_length_mmYesLens focal length in millimeters
apertureYesLens aperture (f-number, e.g. 2.8)
distance_mYesSubject distance in meters
sensor_width_mmNoCamera sensor width in mm (default 36 for full frame)

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?

With no annotations, the description must fully convey behavioral traits. It only states what the tool calculates and returns, omitting details like error handling, default behaviors, or constraints (e.g., on parameter ranges). This is insufficient for a complete understanding.

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

Conciseness5/5

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

The description is two sentences, front-loading the core purpose and outputs, then directing to related tools. No extraneous content makes it efficient and easy to parse.

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 the tool has four parameters (all documented in schema) and an output schema mentioned in the description, completeness is adequate. However, missing transparency details (behavior, edge cases) and lack of annotations lower the score. It is minimally viable.

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?

The input schema has 100% description coverage for all four parameters, explaining units and defaults. The tool description adds no additional parameter information beyond the schema. Per guidelines, baseline is 3 when coverage is high, so this score is appropriate.

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 calculates depth of field, near/far focus limits, and hyperfocal distance for a camera lens. It includes the output format, making the purpose unambiguous. While sibling differentiation is not explicit, the bundle reference provides context, earning top marks.

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 mentions related 'photographie' calculators via list_bundles, which contextualizes usage but does not explicitly state when to use this tool versus alternatives. No when-not or exclusion criteria are given, resulting in an implied but not explicit guideline.

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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