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CrateDrop

Dig a crate of random records

dig_crate
Read-only

Returns 1 to 10 random records from CrateDrop, optionally filtered by genre (e.g. Jazz, Funk / Soul, Electronic, Hip Hop, Reggae, Latin), style (e.g. Bossa Nova, Boogaloo, Deep House, Dub, Library), decade (e.g. 1970) and country (e.g. Brazil, Japan, Nigeria). Each record has artist, title, year, label, styles, Discogs link and a CrateDrop link that plays it. Free.

Input Schema

NameRequiredDescriptionDefault
countNoHow many records, 1 to 10 (default 5)
genreNoDiscogs genre, e.g. Jazz or Funk / Soul
styleNoDiscogs style, e.g. Boogaloo
decadeNoFirst year of the decade, e.g. 1970
countryNoCountry of release, e.g. Brazil

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the readOnly/openWorld annotations, the description adds genuinely useful traits: results are random and vary per call (consistent with idempotentHint=false), the count is capped at 1-10, no auth or payment is needed ('Free'), and it enumerates exactly which fields come back. It doesn't state a default count in the prose (that lives only in the schema) or discuss any rate limits.

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?

It is a single dense sentence, but the key facts (random, 1-10, source, optional filters) are front-loaded and every clause carries information. The parenthetical example lists are long and could be trimmed slightly, but they serve the no-enum schema and don't feel like filler.

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?

With no output schema, the description carries the return-value burden and does so explicitly, naming artist, title, year, label, styles, Discogs link and a playable CrateDrop link. Combined with the count range, optional filter list and free access, an agent has everything needed to call this correctly on the first try.

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 coverage is already 100%, so this is above the baseline-3 case: the description goes further by listing plausible values for genre, style, decade and country (Jazz, Funk / Soul, Bossa Nova, 1970, Brazil, Japan, Nigeria), which matters because the schema defines no enums. This effectively communicates the accepted domain vocabulary that the schema leaves open.

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 ('Returns 1 to 10 random records from CrateDrop') and immediately bounds the output size and the randomization. It then names every filter dimension and what each record contains, so an agent knows exactly what it gets without opening the schema. There are no siblings to disambiguate against.

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

Usage Guidelines4/5

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

It clearly frames the filters as optional and gives concrete example values for each, which tells the agent how to narrow results when desired. 'Free' also signals there is no cost barrier to calling it. It stops short of explicit when-to-use/when-not guidance or rate-limit context, but with no sibling tools there is little to route against.

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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