Skip to main content
Glama
RBV801

recipal-mcp-unofficial

by RBV801

update_recipe

Update a recipe's attributes by providing a recipe ID and a fields object with key-value pairs. Use get_recipe to identify exact attribute names, then submit changes.

Instructions

Update a recipe's attributes. PUT /recipes/{id}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYesOpen key/value object of attributes. Keys are passed straight through to the ReciPal API namespaced under the resource (e.g. {name, package_yield_quantity, package_yield_unit, servings, packages, suggested_serving, sku, preparation, visual_unit_of_measure}). Call get_recipe on an existing recipe first to see the exact attribute names this account uses. Note that tags cannot be set here -- ReciPal accepts the request and silently ignores a tags string, and errors on other shapes. Tags do carry forward through scale_recipe when cloning a tagged template.
as_jsonNo
recipe_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.2

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It adds useful behavioral detail: tags are silently ignored or error depending on shape, and keys are passed through to ReciPal namespaced under the resource. However, it does not disclose whether the update is partial or full replacement, what the response contains, or any side effects or permissions.

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?

The core description is a single front-loaded sentence with the endpoint, and the longer parameter description is dense with useful caveats rather than fluff. The scale_recipe note is slightly tangential but not wasteful.

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

Completeness3/5

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

Given no output schema and no annotations, the description should cover return/error behavior and update semantics; it does not. But it does provide enough field-level guidance and a prerequisite for an agent to likely call the tool correctly for the main use case.

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

Parameters3/5

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

The fields parameter is richly explained with example keys, namespacing behavior, and a get_recipe first instruction, compensating for low schema coverage. However, as_json is left undocumented, and recipe_id only appears by name and in the URL pattern, so the description does not fully compensate for the 33% schema coverage.

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 the exact operation: updating a recipe's attributes, reinforced by the PUT /recipes/{id} endpoint. The resource (recipe, not recipe_ingredient or ingredient) and action are unambiguous, distinguishing it from siblings like update_recipe_ingredient and create_recipe.

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 description implies usage for modifying an existing recipe and gives a practical prerequisite (call get_recipe first to see account-specific attribute names). It does not explicitly say when to prefer this tool over alternatives such as create_recipe or scale_recipe, and only notes an exclusion for tags.

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