Skip to main content
Glama

DropTrack Get Track Submission Opportunities

droptrack_get_track_submission_opportunities
Read-only

Return structured promotion/submission opportunities personalized for one track: record labels, DJs, bloggers, and playlist curators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trackIdYesTrack ID to match against DropTrack submission opportunities
genreSlugsNoOptional additional genre slug filter
searchQueryNoOptional company/name search filter
accountTypesNoSubmission opportunity categories to match against the track
countryCodesNoOptional ISO-2 country code filter
countrySlugsNoOptional country slug filter
limitPerTypeNoMaximum matched opportunities to return per account type
guaranteedListenNoOnly return opportunities with guaranteed listen or paid-feedback options

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoStructured DropTrack result returned by this tool

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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 covered without help from the description. The description adds that results are 'structured' and 'personalized,' but that describes output shape rather than behavior. No side effects, rate limits, pagination details, or other behavioral traits are disclosed, though an output schema exists to cover return structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, front-loaded sentence that names the action, resource, scope, and result categories without any filler. Every word earns its place, and the core purpose is immediately clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only query tool with a full output schema and 100% parameter schema coverage, the description nails the core purpose and scope. The only notable gap is the absence of an explicit pointer to the sibling browse tool for when the user does not have a specific track in mind, but that is an enhancement rather than a critical omission.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all eight parameters already have descriptive text. The tool description adds no parameter-specific meaning beyond naming the result categories that map to accountTypes; that's marginal on top of the schema. The baseline of 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Return') and a clear resource: structured promotion/submission opportunities personalized for one track, and it enumerates the categories (record labels, DJs, bloggers, playlist curators). It clearly conveys what the tool does, but it does not explicitly contrast itself with the sibling 'browse_submission_opportunities' tool, so it doesn't fully differentiate on its own.

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

Usage Guidelines3/5

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

The phrase 'personalized for one track' implies the intended use case—use this when you have a specific trackId and want matched opportunities—but the description gives no explicit when-to-use vs. alternatives guidance, no exclusions, and no mention of the browse tool for non-track-specific discovery. The usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation3/5

Most tools target distinct resources and actions, but several clusters are easy to confuse: get_track_analysis vs get_track_analytics vs get_track_tags, plus analyze_audio/request_track_tagging/auto_tag_tracks overlap in the audio-analysis/tagging space. The descriptions do help separate them, so careful agents can disambiguate, but the naming alone creates real misselection risk.

Naming Consistency4/5

All tools share the droptrack_ prefix, use snake_case, and follow a verb-first noun pattern, with list for collections and get for single items. Minor inconsistencies exist—add_contact vs create_contact_list, browse vs list, auto_tag_tracks—but the overall convention is predictable and readable.

Tool Count2/5

At 55 tools this is far beyond the recommended 3-15 range and well over the 25+ threshold. Many tools are near variants of each other, especially company-level vs label-level ads, analytics, and wallet tools, inflating the surface area and making selection harder.

Completeness3/5

The set covers many domains and some workflows are complete, such as album art generation/polling/acceptance/deletion and track tagging request/poll/apply. However, core lifecycle gaps remain: no update or delete for campaigns, contacts, or contact lists, no playlist mutation tools, and AI press-release/bio workflows end at polling without a save or publish step.