Add all ingredients from a recipe to a shopping list, simplifying meal prep by compiling everything you need in one place.
Add all ingredients from a recipe to a shopping list.
Args: list_id: Shopping list ID recipe_slug: Recipe slug to add ingredients from
| Name | Required | Description | Default |
|---|---|---|---|
| list_id | Yes | ||
| recipe_slug | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only states the action and arguments. It does not explain behavior around duplicates, missing recipes, invalid list IDs, or whether existing shopping list contents are affected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core action, followed by a compact Args block. There is no redundant or wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only two simple parameters and an output schema, so the core invocation details are covered. Missing context about when to use it versus add_shopping_list_item and what side effects may occur leaves notable gaps for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides brief definitions for both parameters, which adds meaning beyond the schema's bare string types. However, the explanations are minimal and mostly restate the parameter names, so they provide only basic semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Add all ingredients from a recipe to a shopping list.' This clearly communicates the operation and distinguishes it from sibling tools like add_shopping_list_item, which adds an individual item rather than all recipe ingredients.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. There is no mention of add_shopping_list_item for single-item additions or any exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.