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DropTrack Validate Campaign Draft

droptrack_validate_campaign_draft
Read-only

Read-only preflight for a campaign draft before using DropTrack Send Test. Requires the expected playlist and contact list, supports normalized-email exclusions from linked lists and exact saved recipient snapshots from prior campaigns, and verifies draft state, audience persistence, subject, optional signoff, Reply-To/test-recipient routing, and outbound U+2014 em-dash safety. This tool does not send email or launch the campaign.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaignIdYesThe exact campaign draft ID
expectedSignoffNoOptional exact signoff text that must appear in the message
expectedSubjectNoOptional exact subject guard
expectedPlaylistIdYesThe playlist ID the draft must contain
expectedContactListIdYesThe contact list ID the draft must contain
expectedExcludedCampaignIdsNoPrior campaign IDs whose exact saved recipient snapshots must be absent from the saved draft audience
expectedExcludedContactListIdsNoLinked contact list IDs whose normalized-email members must be absent from the saved draft audience

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

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false; the description reinforces this with 'Read-only preflight' and 'This tool does not send email or launch the campaign,' then adds detail beyond the annotations about what is actually verified (audience persistence, exclusion semantics, routing, em-dash safety). No contradiction with annotations.

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?

Three sentences, each load-bearing: front-loaded purpose and workflow position, then the verification scope, then a single-sentence non-action disclaimer. There is no filler, no restatement of schema field names, and no redundant security boilerplate.

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 tool with 7 simple-typed parameters, 3 required, an output schema present, and full schema parameter documentation, the description covers purpose, workflow timing, verification scope, and safety profile. The only unstated element is how validation failures surface, but the output schema carries the return-structure burden, so nothing essential is missing.

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%, and the schema already documents all seven parameters including the exclusion-array semantics. The prose only paraphrases the parameter concepts (expected playlist/contact list, normalized-email exclusions, saved recipient snapshots) without adding syntax or format detail, so the baseline of 3 applies.

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 pairs a specific verb-resource construction ('Read-only preflight for a campaign draft') with an exact workflow position ('before using DropTrack Send Test'). It further disambiguates by enumerating the verification scope (draft state, audience persistence, subject, signoff, Reply-To/test-recipient routing, em-dash safety) and explicitly negating sending/launching, so an agent can distinguish it from retrieval, creation, and send siblings.

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 explicit when-to-use context, placing the tool as a preflight immediately before DropTrack Send Test, and states the operational prerequisites (expected playlist and contact list). It does not explicitly name alternative validation or read-only siblings (e.g., droptrack_get_campaign_details) or give when-not-to-use exclusions, so it stops short of full alternative routing.

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.