recipe_searchSearch Spoonacular recipes with complex filters passed as query params (query keyword, cuisine, diet, intolerances, includeIngredients, excludeIngredients, maxReadyTime, sort, etc.). Returns recipe id, title, image, and ready-in minutes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, non-destructive behavior. The description adds value by disclosing that filters are passed as query parameters and that the response includes concise summary fields (id, title, image, ready-in minutes), which helps set expectations beyond the annotations. It does not mention rate limits or pagination, so not a 5.
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?
Two sentences, front-loaded with the core purpose, then a compact enumeration of filters and return fields. Every clause is informative and no words are wasted.
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?
Given the annotations and the presence of an output schema, the description adequately covers the tool's basic contract. It lists the major filter options and return fields, and the schema examples provide additional context. However, it lacks details on pagination, default result counts, or how certain filters are formatted, which keeps it from being fully complete for a complex search API.
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 input schema has no explicit properties, only examples, so the description carries the burden of parameter meaning. It names many relevant parameters (query, cuisine, diet, intolerances, includeIngredients, excludeIngredients, maxReadyTime, sort) and mentions 'query params'. It does not explain value formats or syntax for more complex filters, so it is helpful but not exhaustive; baseline 4 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 opens with the specific verb 'Search' and identifies the resource as 'Spoonacular recipes'. It enumerates the key filtering dimensions (query, cuisine, diet, intolerances, time, sort) and clearly states the return fields (id, title, image, ready-in minutes), distinguishing this tool from sibling tools like recipe_information or recipe_random.
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 conveys that this tool is for searching recipes with rich filters, which is clear context for when to choose it. However, it does not explicitly mention alternatives or when not to use it (e.g., use recipe_information for full details), so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tool set bundles three unrelated domains, and within them several tools are near-indistinguishable: ask_pipeworx_beta is explicitly identical to ask_pipeworx, ask_pipeworx_grounded overlaps with validate_claim, bet_research/polymarket_edges/polymarket_arbitrage all target betting opportunities, and meal_plan_generate duplicates meal_plan_week. The aspect-specific recipe fetchers (ingredients/nutrition/summary/taste) also blur with recipe_information.
Most tools follow a reasonable snake_case verb_noun pattern (recipe_search, resolve_entity, compare_entities, unsubscribe), and each cluster (recipe_*, polymarket_*, ask_pipeworx*) is internally consistent. However, conventions fragment across clusters — bare verb memory tools (remember, forget, recall), the ask_pipeworx_beta/_grounded suffix family, and the odd generate_llms_txt — so no single predictable scheme governs the whole surface.
49 tools is far too many for a coherent surface, and crucially the count is misaligned with the server's stated identity: only 18 of 49 tools actually belong to the Spoonacular food domain, while 27 are Pipeworx data/prediction-market tools and 3 are generic memory utilities. The server appears to be three products mashed into one.
For the core Spoonacular food domain the surface is reasonably complete — search for recipes/products/ingredients, detail fetchers, meal plans, wine pairing, and unit conversion all exist. But the overwhelming presence of unrelated Pipeworx and memory tools makes the server's actual purpose ambiguous, and gaps are hard to assess when the food tools share the namespace with SEC filings and Polymarket arbitrage.