fitatu-api

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Set the daily goals

set_targets

DestructiveIdempotent

Set daily calorie and macro goals, adjust water glass size, or revert to automatic Fitatu-calculated targets. Changes apply from today; earlier days keep their goals.

Instructions

Change the user's daily goals from today on; earlier days keep theirs. energy_kcal sets a manual calorie goal. protein_pct, fat_pct and carbohydrate_pct set the macro split as whole percent of the energy, all three summing to 100; the grams follow from the energy. With energy_kcal alone the current split stays, or 20/30/50 when the account has none (say so); the percentages alone keep the current energy, as a manual goal. automatic true goes back to the goal Fitatu calculates from the user's profile, with no energy_kcal or percentages. water_glass_ml is the glass size water is counted in (get_water's glass_ml). Returns the goals now in effect as get_targets gives them, plus automatic, glass_ml and previous: the arguments that put back what this call changed, with no water_glass_ml when there was no glass size (that cannot be put back). data.ok says Fitatu's reply shows the change.

Input Schema

TableJSON Schema

Name	Required	Description
`fat_pct`	No	Fat's share of the energy goal in whole percent (not body fat).
`automatic`	No	true: back to the goal Fitatu calculates. Only true, and not with energy_kcal or the percentages.
`energy_kcal`	No	Daily calorie goal in kcal; makes the goal manual. Convert kJ first: 1 kcal = 4.184 kJ.
`protein_pct`	No	Protein's share of the energy goal in whole percent; with fat_pct and carbohydrate_pct, summing to 100.
`water_glass_ml`	No	Size of one glass in ml.
`carbohydrate_pct`	No	Carbohydrate's share of the energy goal in whole percent.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes
`data`	No
`error`	No	describe_error() of what went wrong; docs/AGENTS.md, Results and errors.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 16, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations declare destructiveHint=true and idempotentHint=true, yet the description adds substantial behavior beyond them: history before today is preserved, a manual-vs-calculated mode switch, the fallback 20/30/50 split, that the returned 'previous' arguments can restore the change, and that water_glass_ml cannot be restored when none existed. It also explains what data.ok means, which no structured field conveys.

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?

Front-loads the verb and scope, and every clause carries real information about defaults, interactions, or reversibility. It is dense to the point of being a wall of semicolon-joined clauses, which slightly hurts scannability for six parameters.

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 mutation tool with an output schema and full annotation coverage, this is complete: it explains effects on existing data, mode interactions, defaults, and how to undo the change. Nothing an agent needs to invoke it correctly appears to be missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description goes well past per-field docs by defining cross-parameter semantics the schema cannot express: the three percentages must sum to 100, grams are derived from energy, and omitting a group changes what defaults apply (current split stays, or 20/30/50 when none). This is genuine added meaning, not repetition.

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 and resource ('Change the user's daily goals') with an explicit temporal scope ('from today on; earlier days keep theirs'), which is exactly the scope detail needed to distinguish this setter from the read-only get_targets. An agent can tell what it does and what it does not touch without opening the schema.

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?

Gives clear conditional guidance for each mode (energy_kcal alone, percentages alone, automatic true, water_glass_ml) including defaults when the account has no split and that automatic cannot be combined with energy_kcal or percentages. It does not explicitly frame when to call this versus e.g. get_targets, but the context is fully actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.