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LinkedIn campaigns

linkedin_campaigns
Read-only

Campaign groups and campaigns with status, type, objective, daily/total budget, bid (cost type and amount or automated bidding), run schedule and period spend/results. Use to find IDs before changes.

Input Schema

NameRequiredDescriptionDefault
detailNosummary (default): headline numbers and the top 5 rows — right for a specific question or a quick look. full: every row and section — only when the user asks for a full report, a complete list or all the details.
folderNoClient folder name.
statusNoDefault all (not archived or removed).
accountNoLinkedIn ad account name or ID. Optional when only one is enabled.
end_dateNoYYYY-MM-DD.
languageNoLanguage of the card: the language the user is writing in (ar for any Arabic dialect).
date_rangeNoDefault LAST_30_DAYS.
start_dateNoYYYY-MM-DD (with end_date).
campaign_groupNoCampaign group name or ID to filter by.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

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, destructiveHint=false, and openWorldHint=true, so the safety profile is fully covered by structured data. The description adds value by listing what is returned and by signalling this is a lookup step before mutations, but it says nothing about pagination, account scoping, or how campaign groups and campaigns are combined in the result.

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?

Two short sentences: a dense but front-loaded field inventory followed by the actionable routing hint. No filler, no restatement of the title.

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?

With 9 all-optional parameters, no output schema, and read-only annotations, the description adequately tells the agent what rows and metrics come back, which compensates for the missing output schema. The main residual gap is not clarifying how campaign groups are nested relative to campaigns in the response.

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 every parameter including the detail and date_range enums is already documented in the schema. The description's attribute list (budget, bid, schedule) describes output rather than parameter meaning, so it adds little beyond the baseline for a fully documented schema.

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 names the resources (campaign groups and campaigns) and enumerates the attributes returned (status, type, objective, budgets, bid, schedule, spend/results), which lets an agent distinguish it from linkedin_performance or linkedin_breakdown. The verb is only implied ('Campaign groups and campaigns with...'), so it reads as an inventory of returned fields rather than a stated action.

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?

'Use to find IDs before changes' gives one clear use case, but it never says when to prefer this over sibling tools such as linkedin_performance, linkedin_ads, or linkedin_breakdown. The detail enum guidance in the schema covers summary-vs-full depth, but routing between LinkedIn tools is left to inference.

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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