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rollecode

Cronometer MCP server

by rollecode

retire_custom_food

DestructiveIdempotent

Retire a custom food from Cronometer to stop it appearing in new entries while preserving existing diary entries. Use retired=False to restore it if needed.

Instructions

Retire a custom food so it stops being offered for new entries.

This is how Cronometer removes a food; there is no delete. Diary entries that already use it keep working. Pass retired=False to bring it back.

Args: food_id: The custom food's ID. retired: True to retire, False to restore.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
food_idYes
retiredNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.9.2

TDQS

A4.8/5.0
Behavior5/5

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

With annotations already marking the operation as destructive and idempotent, the description adds meaningful behavioral detail: existing diary entries that use the food keep working, and the operation is reversible by passing retired=False. This explains exactly what is destroyed and what is preserved, going well beyond the annotation hints.

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 tightly structured with the core action first, followed by lifecycle context, then an Args section. Every sentence contributes meaningful information and nothing is redundant or verbose. The format is easy for an agent to scan and extract call-relevant details.

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 two-parameter mutation tool with rich annotations and an output schema, the description is complete. It explains the operation, the no-delete behavior, the reversibility, and both parameters, so an agent has everything needed to invoke the tool correctly without additional inference.

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 description coverage is 0%, so the description must fully explain both parameters. It does: food_id is identified as the custom food's ID, and retired is explicitly described as 'True to retire, False to restore.' This fully compensates for the lack of schema-provided descriptions.

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 opens with a specific verb and resource: 'Retire a custom food so it stops being offered for new entries.' It further clarifies that this is Cronometer's removal mechanism and there is no delete, clearly distinguishing the tool from a hard-delete operation while making its purpose unmistakable.

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 provides clear context for when to use the tool: when a custom food should no longer be offered for new entries. It also explains the restoration path via retired=False, which gives the agent the full lifecycle context. It does not explicitly name sibling alternatives, but states 'there is no delete', which is sufficient exclusion guidance.

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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