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tresor4k

macalc

calculate_bread_hydration

Calculate baker's hydration percentage from flour and water weights to classify dough as firm, standard, or wet.

Instructions

Compute baker's hydration % = water/flour×100. Use for bread recipe analysis. Inputs: flour g, water g. Returns hydration % and dough type (firm/standard/wet). See list_bundles for related 'cuisine' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flour_gramsYesFlour weight grams
water_gramsYesWater weight grams

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.
Behavior4/5

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

No annotations are provided, so the description fully discloses behavior: it computes hydration percentage and returns dough type. Since it is a simple calculation, no side effects or destructive actions exist. The description is transparent about what it does.

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 extremely concise, with two sentences plus a formula. It front-loads the purpose and includes the formula, input summary, output summary, and a pointer to related tools. Every sentence is valuable and no extraneous content.

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

Completeness5/5

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

For a simple two-parameter calculation tool with an output schema, the description covers all needed aspects: purpose, formula, inputs, outputs, and even a reference to related tools. No gaps remain.

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?

Input schema has 100% description coverage, so the baseline is 3. The description adds 'Inputs: flour g, water g' and the formula, which reinforces parameter meaning but does not add significant new information beyond the schema.

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 provides the exact formula and explicitly states it computes baker's hydration percentage for bread recipe analysis. The verb 'compute' and the formula make the purpose clear and distinguishable from the many sibling calculate_* tools.

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

Usage Guidelines4/5

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

The description advises 'Use for bread recipe analysis,' which gives clear context. It also points to list_bundles for related calculators, implying alternatives. However, it does not explicitly state when not to use this tool, but the context is sufficient.

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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