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linkedin-pilot

linkedin-pilot

by juanpacj-wq
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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linkedin_posts_read

Fetch LinkedIn feed posts or a profile's recent activity with an optional source and limit, enabling AI agents to analyze or engage with current content.

Instructions

Lee publicaciones del feed ("feed") o la actividad reciente de un perfil.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "linkedin_posts_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
sourceNo"feed" (por defecto) o URL/identificador de un perfil.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it only implies a read via 'Lee'. It says nothing about authentication/session requirements, rate limits, pagination, result ordering, or what happens when a profile identifier is invalid — all relevant for a scraper-style tool.

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

Conciseness4/5

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

A single front-loaded sentence with no filler. It is efficient, though the extreme brevity edges toward under-specification rather than genuine conciseness.

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

Completeness2/5

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

For a 2-parameter tool with no annotations and no output schema, the description should explain return shape, pagination, and the meaning of 'limit', but it does none of these. It leaves core operational questions unanswered.

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

Parameters2/5

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

Schema coverage is only 50%: 'source' is documented in the schema, but 'limit' (1-50) is undocumented everywhere, and the description repeats the feed/profile distinction already present in the schema. It fails to compensate for the coverage gap by explaining what 'limit' bounds.

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?

States a specific verb ('Lee') and resource ('publicaciones') and clarifies the two scopes it covers: the feed or a profile's recent activity. This is clear and interpretable, but it never distinguishes itself from nearby siblings like linkedin_profile_read or linkedin_profile_sections, so an agent must infer the boundary.

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?

It names the two data sources (feed vs profile activity) but gives no when-to-use guidance, no prerequisites, and no routing against alternatives such as linkedin_profile_read or linkedin_browser_snapshot. The agent is left to guess which reading tool to pick.

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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