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get_diary_day

Read-only

Read your FatSecret food diary for a specific day, grouped by meal with calories, macros, totals, targets, and remaining amounts. Use it to answer what you ate today or how much you have left.

Instructions

Read the User's Food Diary for one Diary Day.

Returns the Food Entries grouped by Meal (name, amount, kcal and Macros), the day's totals, the User's Daily Targets and what remains of them. Use it for questions like "what have I eaten today?" or "how much is left?". Past days reuse entries already read during this server session, for up to twelve hours. Today is always fresh. Set refresh=true when the User requests fresh data or says they changed this past day in the FatSecret app.

Input Schema

NameRequiredDescriptionDefault
refreshNo
diary_dayNoThe Diary Day, as YYYY-MM-DD. Omit for today in the User's timezone.

Output Schema

NameRequiredDescriptionDefault
mealsYesMeals that have Food Entries, in the order of the day.
totalsYes
diary_dayYes
remainingYesDaily Targets minus totals; negative once a target is exceeded.
daily_targetsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true; the description adds the non-obvious caching contract that past days may be up to twelve hours stale while today is always fresh. That directly changes whether an agent trusts the result, and the refresh=true escape hatch plus its trigger condition is spelled out, not left implicit.

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?

Front-loaded with the action, then return contents, then usage examples, then the caching caveat, in a natural decision order. Every sentence carries weight; the only mild redundancy is restating return fields that the output schema already enumerates.

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?

With an output schema present and readOnlyHint set, the description covers what remains: scope of one day, cache freshness, and the refresh trigger. An agent has everything needed to call it correctly and to judge result staleness.

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

Parameters4/5

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

Schema coverage is only 50% and the undocumented parameter is refresh, which the description fully compensates for by defining its default behavior and the exact user signals that should flip it. diary_day is already covered in the schema as YYYY-MM-DD with today as default, so the description adds little there.

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 ("Read the User's Food Diary for one Diary Day") and enumerates what comes back: entries grouped by Meal, day totals, Daily Targets and remaining amounts. It is unambiguous on its own, but never references the sibling get_period_summary, so the agent must infer that multi-day aggregates belong there rather than here.

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 concrete triggering questions ("what have I eaten today?", "how much is left?") and an explicit refresh condition ("when the User requests fresh data or says they changed this past day in the FatSecret app"). It does not name alternatives or exclusions, so it is clear context rather than full when/when-not routing.

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