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Track influencer

track_influencer

Add a LinkedIn profile to the Influencer Agent and immediately queue a run to collect everyone who engaged with their posts. Example: track linkedin.com/in/johndoe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkedinUrlYesLinkedIn profile URL of the influencer to track (e.g. linkedin.com/in/johndoe or https://www.linkedin.com/in/johndoe)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context beyond that: tracking a profile immediately queues a collection run. It does not cover what happens if the profile is already tracked or how to undo it, but the added side-effect detail is meaningful.

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, front-loaded with the action and its immediate effect, followed by a compact example. No wasted words; every sentence contributes to understanding the tool's behavior.

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?

For a simple one-parameter mutation tool with annotations covering safety and a fully documented schema, the description is complete enough: it names the resource, the effect, and the side effect. It could optionally mention persistence or how to undo tracking, but that is a minor gap given the tool's low complexity.

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?

Schema description coverage is 100%, so the single linkedinUrl parameter is already well documented with format examples. The description's example URL only repeats what the schema already provides and adds no new semantic detail about the parameter.

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?

The description states a specific verb ('Add a LinkedIn profile to the Influencer Agent') and the immediate consequence ('queue a run to collect everyone who engaged with their posts'). This clearly distinguishes it from siblings like find_influencers or run_influencer_agent, which do not add a profile and auto-queue collection.

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?

The description implies the usage context (adding a tracked influencer and collecting engagers), but it never states when to use this tool versus alternatives such as find_influencers, run_influencer_agent, or untrack_influencer. No exclusions or prerequisites are given.

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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