Skip to main content
Glama

Build custom recipes for a pet

generate_recipe

Submit a pet profile and selected food IDs to generate balanced recipe options, reporting any ingredients that could not be included.

Instructions

Fill the pet profile, pick ingredient food_ids, submit, and wait for Balance IT to build N balanced recipe options. Browser-driven; typically 60-90s. Food_ids come from search_foods or list_catalogue. The response includes submitted_food_ids (ground-truth from the form) and missing_from_options (a soft signal that a requested ingredient did not appear in the built recipes; empty in the happy path). Any food_id that could not be added throws a clear error rather than silently dropping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageYes
genderYes
weightYes
speciesYes
age_unitYes
food_idsYes
pet_nameYes
num_optionsNo
weight_unitYes
one_pot_cookingNo
Behavior5/5

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

With no annotations provided, the description carries the full burden of disclosure. It reveals that the tool is 'Browser-driven; typically 60-90s,' explains the response fields (submitted_food_ids and missing_from_options), and clearly states error behavior: 'Any food_id that could not be added throws a clear error rather than silently dropping.' This is exceptional transparency.

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 concise and front-loaded, starting with the action, then providing latency, input provenance, response details, and error behavior in four sentences. Every sentence adds essential information without redundancy.

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?

Despite having 10 parameters, no output schema, and no annotations, the description covers the workflow, expected latency, key response elements, and error handling. It gives a user enough context to use the tool correctly and set expectations, making it highly complete for its complexity.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining the workflow, that food_ids come from other tools, and that N options are built. However, it does not describe all parameters (e.g., one_pot_cooking, weight_unit, age_unit) beyond the schema's enum names, leaving some gaps.

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 clearly states the tool's function: 'Fill the pet profile, pick ingredient food_ids, submit, and wait for Balance IT to build N balanced recipe options.' It uses a specific verb (build) and resource (balanced recipe options), and distinguishes itself from siblings like search_foods, list_catalogue, and calculate_calories by focusing on recipe generation.

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 usage context by stating 'Food_ids come from search_foods or list_catalogue,' which tells the user how to obtain necessary inputs. It implicitly defines the use case (generating recipes) without explicitly naming alternatives, but the integration with other tools gives practical guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/seraphinerenard/balanceit-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server