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Huzaifa-ali

mcp-server-linkedin

by Huzaifa-ali

linkedin_get_post_stats

Get analytics for a LinkedIn post: impressions, clicks, likes, comments, shares. Returns setup instructions if API access is unavailable.

Instructions

Get analytics (impressions, clicks, likes, comments, shares) for a specific LinkedIn post. NOTE: Currently requires Community Management API access (r_member_postAnalytics scope) which must be applied for separately at developer.linkedin.com. Returns instructions on how to gain access if not available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricNoimpressions
post_idYes
end_dateNo
start_dateNo
aggregationNodaily

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses access requirements and fallback returns, but lacks mention of read-only nature, rate limits, or side effects. Some useful context but incomplete.

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 sentences plus a parenthetical note, front-loaded with purpose. No wasted words; appropriate length for the tool's simplicity.

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 5 parameters, 1 required, and existing output schema, the description covers the tool's core purpose and access constraints but omits details on date range or aggregation semantics, leaving some context gaps.

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%, yet the description does not explain any of the parameters (metric, start_date, end_date, aggregation) beyond implicitly indicating post_id identifies a post. Fails to add meaning to the input schema.

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?

Clearly states the verb 'Get' and the resource 'analytics (impressions, clicks, likes, comments, shares) for a specific LinkedIn post'. Distinguishes from sibling 'linkedin_get_all_stats' by focusing on a single post.

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?

Provides prerequisite access scope and fallback behavior (returns instructions if not available), but does not explicitly guide when to use this tool vs. alternatives like linkedin_get_all_stats.

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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