Canadian grocery flyer deals and recipes by item, store, postal code, cuisine, or diet. No auth.
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Average 4.2/5 across 3 of 3 tools scored.
Each tool targets a clearly distinct action: searching flyer deals, searching recipes, and retrieving recipe details. There is no meaningful overlap between grocery deals and recipe-related tools.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_flyer_deals, get_recipe, search_meals. This makes the API predictable and easy to navigate.
Three tools is a small but reasonable set for a focused grocery deals and recipes server. It covers the core read-oriented workflows without unnecessary bloat, though a couple more niche tools could expand usefulness.
The domain is covered at a basic level: search and detail retrieval exist for both recipes and flyer deals. Minor gaps like listing stores or browsing recipe categories are present but not blocking for typical usage.
get_flyer_dealsFind grocery dealsASearch current Canadian grocery flyer deals by item name or store.
Covers FreshCo, Costco, Walmart, Food Basics, and more. All returned deals are currently valid and from the latest successful flyer fetch per store.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results | |
| query | No | Item name to search deals for (e.g. paneer, milk, rice) | |
| store | No | Filter by store name (e.g. FreshCo, Costco) | |
| postal_code | No | Canadian postal code for location-aware deals (e.g. L4B1C3) |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as readOnly and non-destructive. The description adds valuable behavior beyond that: returned deals are guaranteed to be currently valid and are sourced from the latest successful flyer fetch per store. This sets expectations about result freshness and coverage.
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 compact and front-loaded with the core search action, then adds store coverage and freshness guarantees. Every sentence contributes practical information with no filler or repetition of the title.
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 description, combined with the exhaustive input schema and available readOnly annotations, supports correct invocation well. It lacks explicit guidance on result ordering or empty-query behavior, but the output schema and the stated valid-date guarantee cover most agent needs.
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?
Schema coverage is 100%, so every parameter already has descriptions and examples. The tool description reinforces the query and store concepts but does not add significant new meaning beyond the schema. Baseline 3 is appropriate.
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 states a specific verb, resource, and scope: 'Search current Canadian grocery flyer deals by item name or store.' This clearly distinguishes it from sibling tools like get_recipe and search_meals, since they target recipes/meals rather than flyer deals.
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?
The description communicates a clear usage context: use this for current Canadian grocery flyer deals, searchable by item, store, and postal code. It does not explicitly name alternatives or state when not to use it, but the subject matter is clearly different from the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recipeGet recipeAGet full recipe details for a specific meal, including scaled ingredients and steps.
| Name | Required | Description | Default |
|---|---|---|---|
| meal_id | Yes | Meal ID from search_meals (UUID) |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is well covered. The description adds a useful statement about returning scaled ingredients and steps, which clarifies what the operation yields. No contradiction exists between description and annotations.
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 one focused sentence that says exactly what the tool does and what it returns. It is front-loaded with the main purpose and includes no filler or repetition. Every part earns its place.
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?
This is a simple, single-parameter read-only tool with a rich output schema, so the description does not need much more. The parameter is fully documented in the schema and the purpose/return content is clearly stated. The agent has enough context to select and invoke this tool correctly.
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?
Schema description coverage is 100% and the meal_id parameter is already documented well as 'Meal ID from search_meals (UUID).' The description references the meal concept but adds no significant parameter details beyond the schema. Baseline 3 is appropriate because the schema carries the semantic weight.
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 states a specific verb and resource: 'Get full recipe details for a specific meal.' It also specifies the content that distinguishes this from other tools — 'scaled ingredients and steps.' This clearly separates it from search_meals and get_flyer_deals.
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?
The description implies this is for fetching details for one specific meal rather than searching or browsing. The input schema reinforces the intended flow by requiring a meal_id from search_meals. It could be stronger with an explicit when-not-to-use statement, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_mealsSearch mealsASearch NoshUp's recipe catalogue by cuisine, dietary preference, ingredient, or meal type.
The query matches both meal names and recipe ingredients.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results | |
| query | No | Dish name, cuisine type, or ingredient to search for | |
| cuisine | No | Filter by cuisine | |
| dietary | No | Dietary constraints (vegetarian, vegan, gluten_free, nut_allergy) | |
| meal_type | No | Filter by meal type |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and non-destructive, so the safety profile is covered. The description adds useful behavioral context by explaining that the query searches both meal names and recipe ingredients. There is no contradiction, and no surprising mutation or side effect is implied.
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 key action and resource. It adds only one high-value sentence about query matching, with no filler or redundant wording.
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?
For a read-only search tool with an output schema and fully self-explanatory input schema, the description and annotations provide all necessary operational context. The tool is simple, has no required parameters, and is already supported by structured metadata that fills any remaining gaps.
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?
Input schema coverage is 100%, base credit applies. The description adds valuable extra semantics by clarifying that the query parameter applies to both meal names and ingredients, which is not stated in the schema's 'Dish name, cuisine type, or ingredient to search for' description. It does not introduce new parameter behavior beyond that, but it usefully complements the schema.
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 clearly identifies a specific verb ('Search') and resource ('NoshUp's recipe catalogue'), and further clarifies the scope by stating the query matches meal names and recipe ingredients. This distinguishes it from sibling tools like get_recipe, which retrieves a single recipe, and get_flyer_deals, which is unrelated.
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?
The description implies use when searching or exploring recipes by cuisine, diet, ingredient, or meal type, but it gives no explicit when-not-to-use guidance or mention of sibling alternatives. The context is understandable, but the guidance is still left largely implicit.
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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