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campaignstack_get_ad_dashboard

Read-onlyIdempotent

Get the ads dashboard for a workspace: connection status, spend/impression/click/lead totals, per-account breakdown, and a daily trend. Dates are YYYY-MM-DD; omit them for the last 30 days. For raw daily rows per entity use campaignstack_get_ad_analytics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateNoYYYY-MM-DD. Defaults to today.
platformNoAd platform. Only 'linkedin' is supported today.linkedin
startDateNoYYYY-MM-DD. Defaults to 30 days ago.
workspaceIdNoDefaults to the API key's workspace

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by laying out exactly what the response will contain (connection status, totals, per-account breakdown, daily trend) and the date defaulting behavior. It does not mention auth or rate limits, but for a read-only dashboard tool that is acceptable.

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 earning its place: the purpose and expected output are front-loaded, the date convention is concise, and the sibling distinction is a single clear clause. There is no fluff or redundancy.

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?

There is no output schema, but the description compensates by listing the dashboard's major sections. It also explains the default date range, and the schema fully documents all optional parameters. Combined with the annotations' safety profile, an agent has everything needed to select and invoke this correctly.

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%, with each parameter (startDate, endDate, platform, workspaceId) having its own description and default values. The description's date guidance ('omit them for the last 30 days') is largely a restatement of those schema defaults, adding little genuinely new parameter meaning. This matches the baseline of 3 for high schema coverage.

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 states a specific verb and resource: 'Get the ads dashboard for a workspace,' and enumerates the dashboard's components (connection status, spend/impression/click/lead totals, per-account breakdown, daily trend). It also explicitly distinguishes itself from the sibling campaignstack_get_ad_analytics by directing raw per-entity row requests there, making its scope sharp.

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

Usage Guidelines5/5

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

The description gives an explicit when-to-use instruction relative to the main alternative: use campaignstack_get_ad_analytics for raw daily rows per entity. It also provides a concrete invocation rule for the default 30-day window by telling the agent to omit dates. This is strong routing guidance.

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

A3.6/5.0
Disambiguation3/5

Many tools share the same verb prefix (create_, list_, update_, get_) across closely related resources, so pairs like add_lead_to_external_list vs add_lead_to_sequence, create_signal_agent vs create_signal_watch, and approve_review vs approve_content_post can be confused. The descriptions are unusually detailed and cross-referenced, which mitigates but does not eliminate the ambiguity inherent in a 282-tool surface.

Naming Consistency4/5

Virtually every tool follows the campaignstack_verb_noun snake_case pattern, which is highly predictable. Minor deviations exist: destructive operations mix remove_ and delete_ (remove_lead_list vs delete_campaign), AI generation uses both craft_ and generate_, and the seo_/search_console_ subdomains introduce a second prefix convention.

Tool Count1/5

282 tools is an extreme mismatch by any reasonable standard, exceeding the 50+ threshold by more than 5x. Even for a full B2B outreach platform, this surface is far too large and would be better consolidated into higher-level operations or grouped sub-servers.

Completeness4/5

The tool surface is impressively comprehensive, covering campaigns, workflows, leads, content, ads, SEO, integrations, billing, and more with CRUD-level depth. Minor gaps remain: no single-ICP getter, no direct pause/delete for search watches, and no explicit delete for ad campaigns (only archive via update).

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