AIGigLab MCP Server

trigger_linkedin_post_now

Instantly generate and publish a LinkedIn post using your saved settings and available credits.

Instructions

Immediately generate and post content to LinkedIn using your current configuration and available credits.

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": "trigger_linkedin_post_now"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.3.0Jul 15, 2026

TDQS

A3.5/5.0

Behavior3/5

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

No annotations are provided, so the description must carry full burden. It discloses immediate action, credit usage, and use of current config, but does not mention side effects, reversibility, error conditions, or rate limits. Core behavior is captured but lacks depth.

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?

A single sentence that front-loads the action (Immediately generate and post), with no wasted words. Every part of the description is meaningful.

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?

Given no parameters and no output schema, the description covers the essential input (current config, credits) and output (post made). Could mention that this is immediate vs. scheduled, but overall sufficient for a simple trigger tool.

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

Parameters4/5

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

Input schema has no parameters, so description cannot add value beyond what schema already provides. Baseline for 0 parameters is 4, and the description appropriately handles this.

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 action (generate and post) and platform (LinkedIn). It uses specific verb and resource, and while it doesn't explicitly differentiate from siblings, the immediate post action is distinct from read or config tools in the sibling list.

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?

No guidance on when to use this tool versus alternatives like set_linkedin_post_target or update_linkedin_config. The description implies it uses current configuration and credits but does not state prerequisites or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.