droptrack_add_contacts_to_listAdd one or more contacts to an existing contact list.
| Name | Required | Description | Default |
|---|---|---|---|
| listId | Yes | Contact list ID | |
| contactIds | Yes | Array of contact IDs to add |
| Name | Required | Description | Default |
|---|---|---|---|
| result | No | Structured DropTrack result returned by this tool |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, which aligns with the mutation described. The description adds a small precondition ('existing contact list') but does not disclose behavior such as duplicate handling, idempotency, or repercussions for invalid contact IDs. With annotations covering the basic mutation/destruction profile, this is acceptable but not rich.
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?
The description is a single sentence that is clear, front-loaded with the action, and contains no filler. It efficiently communicates the core operation without unnecessary elaboration.
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?
This is a low-complexity, two-parameter write operation with fully documented parameters and an output schema present. The description covers the essential precondition that the list must already exist, though it could have explicitly noted duplicate or invalid contact behavior; overall it is sufficiently complete for correct invocation.
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?
Schema description coverage is 100%, and both parameters are already documented as listId and an array of contact IDs. The description reinforces that multiple contacts can be added, but it does not add meaningful details beyond what the schema already provides, so the baseline score of 3 applies.
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 uses a specific verb ('Add'), a clear resource ('contacts'), and a target context ('existing contact list'). It distinguishes this from sibling tools like droptrack_add_contact and droptrack_create_contact_list by emphasizing the list already exists and that one or more contacts are being added.
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 phrase 'existing contact list' implies the list must already exist before calling this tool, which is useful. However, it does not explicitly state when to use this tool versus alternatives such as droptrack_create_contact_list or droptrack_add_contact, leaving the routing mostly to inference.
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.
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.
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.
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.
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.