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create_linkedin_campaign

Destructive

Create LinkedIn Ads campaigns for B2B advertising by setting objectives, budgets, and targeting company sizes, industries, and job functions.

Instructions

Create a LinkedIn Ads campaign for B2B advertising.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCampaign name
objectiveYesCampaign objective
daily_budgetYesDaily budget in USD
target_company_sizesNoTarget company sizes
target_industriesNoTarget industries (LinkedIn industry codes)
target_job_functionsNoTarget job functions (e.g., 'Marketing', 'Engineering', 'Sales')
Behavior3/5

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

The description doesn't add behavioral details beyond the 'destructiveHint: true' annotation, which already indicates a mutation operation. It lacks context on permissions, rate limits, or what happens upon creation (e.g., campaign status, costs). No contradiction with annotations exists, but the description doesn't compensate for the annotation's limited scope.

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, efficient sentence that front-loads the core purpose without unnecessary words. It's appropriately sized for a tool with good schema coverage and annotations, making every word count.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the destructive annotation and lack of output schema, the description is minimally adequate but incomplete. It doesn't explain the creation outcome, error handling, or integration with sibling tools like 'list_campaigns'. For a mutation tool with behavioral implications, more context would be helpful despite the clear schema.

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?

With 100% schema description coverage, the schema fully documents all 6 parameters, including enums for 'objective' and 'target_company_sizes'. The description adds no parameter-specific information beyond the general B2B context, which is implied but not detailed. This meets the baseline for high schema coverage.

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 the verb ('Create') and resource ('LinkedIn Ads campaign') with a specific context ('for B2B advertising'). It distinguishes from most siblings like 'create_meta_campaign' or 'create_search_campaign' by specifying the LinkedIn platform and B2B focus, though it doesn't explicitly differentiate from all campaign creation tools.

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

Usage Guidelines2/5

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

The description provides minimal guidance, only implying usage for B2B advertising on LinkedIn. It doesn't specify when to use this tool versus alternatives like 'create_meta_campaign' or 'create_display_campaign', nor does it mention prerequisites, exclusions, or typical scenarios beyond the broad B2B context.

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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