mcp-server-fatsecret

Prepare: Edit Food Entry (FatSecret)

fatsecret_prepare_food_entry_edit

Prepare to edit an existing food diary entry by validating new serving, quantity, meal, and reason before saving changes.

Instructions

Dry-run: prepare editing an existing food diary entry.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "foodEntryId": "<foodEntryId>",
      "servingId": "<servingId>",
      "numberOfUnits": "<numberOfUnits>",
      "meal": "<meal>",
      "reason": "<reason>"
    },
    "name": "fatsecret_prepare_food_entry_edit"
  }
}

Input Schema

Name	Required	Description	Default
`meal`	Yes
`reason`	Yes
`servingId`	Yes
`foodEntryId`	Yes
`numberOfUnits`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 17, 2026

TDQS

C2.9/5.0

Behavior2/5

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

The description says 'Dry-run,' which suggests no side effects, but the annotations indicate readOnlyHint=false, implying the tool may write (e.g., create a prepared operation). The description does not clarify the lifecycle (e.g., returning a prepared operation token required for later commit) or any other behavioral traits beyond what annotations already provide.

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 a single concise sentence with no wasted words, but it is under-specified for a tool with 5 parameters and a prepare/commit pattern. It is front-loaded but far too brief to be fully useful.

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

Completeness2/5

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

The tool is part of a prepare/commit workflow (evidenced by sibling tools), but the description does not explain the return value, the need to call commit_prepared_operation afterwards, or how parameters are used. With no output schema and minimal description, the context is incomplete.

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

Parameters1/5

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

Schema description coverage is 0% and the description provides no information about the five required parameters. The parameter names (foodEntryId, servingId, numberOfUnits, meal, reason) are self-descriptive but the purpose of 'reason' and how parameters relate to the edit operation are not explained, leaving significant ambiguity.

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 states the specific action: 'prepare editing an existing food diary entry.' This clearly distinguishes it from create/delete/prepare operations for other resources, and the 'Dry-run' prefix signals this is the preparation step, not the final commit.

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 'Dry-run' label implies this tool is used to validate or prepare an edit before committing, but it does not explicitly state when to use it versus alternatives like commit_prepared_operation or prepare_food_entry_create. The usage context is implied rather than directly stated.

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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