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DropTrack List Label Contacts

droptrack_list_label_contacts
Read-only

List contacts across the label family, with label versus artist ownership annotations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results per page
cursorNoPagination cursor (offset)
artistIdsNoOptional comma-separated company IDs to scope contacts to; omit or use all for the whole visible family
labelCompanyIdNoAdmin-only override: label company ID

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

A3.8/5.0
Behavior3/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that returned contacts include label versus artist ownership annotations, which is useful context, but it does not disclose pagination, authorization nuances, or other behavioral details beyond what the schema and annotations provide.

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?

The description is a single sentence that front-loads the action and resource, then adds the distinguishing output characteristic. There is no repetition of the title or schema details and no filler.

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 list tool with a fully described input schema, an output schema, and safety annotations, the description is nearly complete. The main gap is the absence of guidance on how this relates to sibling contact tools, but the structured metadata covers behavior and parameters adequately.

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?

The input schema covers all four parameters with descriptions at 100% coverage, so the baseline is 3. The tool description does not add substantial parameter-level meaning; it only hints at ownership scoping through the phrase 'label versus artist ownership annotations.'

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 clearly states a specific action ('List contacts') and scope ('across the label family'), plus a distinguishing output trait: label versus artist ownership annotations. It does not explicitly name a sibling tool to differentiate from, but the phrasing is specific enough to separate it from search_contacts or list_contact_lists.

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?

The description gives a clear context for use: when you need contacts across the label family with ownership annotations. It does not explicitly state when to prefer a sibling like search_contacts or when not to use this tool, but the intended usage is evident.

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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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.