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flin-agency

flin-linkedin-ads-mcp

by flin-agency

list_account_intelligence

List company-level account intelligence rows for LinkedIn ad accounts, including performance metrics by company size, industry, or segment. Filter by lookback window, campaign, or ad segments.

Instructions

List company-level account intelligence rows (private LinkedIn API access required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_account_idNo
lookback_windowNoLAST_90_DAYS
ad_segment_idsNo
campaign_idNo
skip_company_decorationNo
page_startNo
page_sizeNo
fieldsNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions the API requirement and omits key traits such as whether the operation is read-only, any pagination behavior, rate limits, or consequences of use. This is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, very concise but at the expense of substance. For a tool with 8 parameters, it should include structured guidance or parameter hints. The extreme brevity here is under-specification rather than effective conciseness.

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

Completeness1/5

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

Given the complexity (8 parameters, no output schema, no annotations), the description is severely incomplete. It does not explain what account intelligence rows are, how parameters interact, or what the output format is. The information provided is insufficient for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning no parameter has a description in the schema. The tool description does not elaborate on any of the 8 parameters (e.g., ad_account_id, lookback_window, fields), providing zero additional meaning beyond their names and basic types.

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 it lists company-level account intelligence rows, specifying the verb and resource. The addition of '(private LinkedIn API access required)' provides a basic distinguishing requirement, but it does not explicitly differentiate from sibling list tools like list_ad_accounts or list_campaigns, preventing a 5.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention when not to use it. The only hint is the API access requirement, which is insufficient for guiding tool selection among the many sibling tools.

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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