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DrinkedIn — licensed bar data

drinkedin_get_cocktail_recipe

Read-onlyIdempotent

Read one published cocktail recipe by name or slug, the same fields as the public page at /cocktails/. drinkedin_list_data_products names the paid cocktail feed and does not deliver rows; GET /api/data/v1/cocktails still needs x402 or a licence when it would return rows. The match is exact on the published name or slug after folding case, accents, and punctuation. It is not a prefix, an ingredient search, or a list. Success returns found and recipe (as structuredContent and as JSON text). recipe carries only the public-page fields, the canonical url, and the page provenance. An unknown name, an unpublished cocktail, or a cocktail with no public slug returns found false, recipe null, and browse_url /cocktails/. No credentials and no payment. Read-only and repeatable.

Input Schema

NameRequiredDescriptionDefault
nameYesCocktail name or slug. Exact match after folding case, accents, and punctuation. Not a prefix and not an ingredient.

Output Schema

NameRequiredDescriptionDefault
foundNo
recipeNo
browse_urlNoPresent when no single public recipe matched

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, and the description adds genuine context beyond them: exact-match folding rules, the success shape (found + recipe), the failure shape (found false, recipe null, browse_url), and that no credentials or payment are required. This is rich behavioral disclosure that complements rather than repeats the annotations.

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?

Front-loaded with purpose and scope, then match semantics, then success/failure shape, then auth. It is dense but nearly every sentence carries routing or contract information; the x402/licence aside is useful but slightly leans into explaining a sibling endpoint rather than this tool.

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?

For a single-param read tool with annotations already covering safety and an output schema present, the description supplies everything an agent needs: exact-match semantics, success and failure contracts, and confirmation that no credentials or payment are involved. Nothing material is left unspecified.

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 100%, so the baseline is 3, but the description contextualizes the single 'name' parameter by restating the folding semantics (case, accents, punctuation) and the negative constraints in the context of matching against published records. It edges above baseline by framing what the match operates on, though it largely echoes the schema's own param text.

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 opens with a specific verb and resource ('Read one published cocktail recipe by name or slug') and ties the returned fields to the public page at /cocktails/<slug>. It explicitly distinguishes itself from drinkedin_list_data_products and GET /api/data/v1/cocktails, so an agent can route correctly without opening another schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage boundaries are stated exhaustively: exact match on published name or slug, explicitly 'not a prefix, an ingredient search, or a list,' and it names the sibling (list_data_products) and endpoint (GET /api/data/v1/cocktails) that would otherwise be confused with it, including the credential/payment condition for the latter.

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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