HeyLead

by D4umak

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

create_post

Destructive

Generate and publish voice-matched social posts to LinkedIn or X to build authority and drive inbound connections.

Instructions

Generate and publish a voice-matched post to LinkedIn, X/Twitter, or both.

Creates posts using your voice signature for social selling.
Builds authority and drives inbound connections across platforms.

Args:
    topic: What to post about (e.g., "share a tip about cold outreach",
        "comment on AI in sales", "share a success story").
    tone: Post tone: "professional", "casual", "thought-leader", "storytelling".
    platforms: Comma-separated platforms: "linkedin", "x", or "linkedin,x".
    image: Path to a photo to attach. LinkedIn only — a tweet is posted
        without it. png, jpg, gif or webp, up to 10MB.
    mode: "autopilot" (publishes immediately).

Input Schema

TableJSON Schema

Name	Required	Default
`tone`	No	professional
`image`	No
`topic`	No
`platforms`	No	linkedin

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.375Sep 18, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already signal read/write and destructive behavior; the description adds valuable behavioral specifics: image is attached on LinkedIn only, a tweet is posted without it, file format/size limits, and mode 'autopilot' publishes immediately. This goes beyond the structured fields.

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?

The main purpose is front-loaded and the Args block is scannable. The sentence 'Builds authority and drives inbound connections across platforms' is promotional rather than informative, but it is brief and does not obscure the operational details.

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 publish action, the description covers what to post, tone options, platforms, image behavior, and immediate publishing. An output schema exists, so return-value details aren't required. The only notable gap is the missing mode parameter in the schema, which leaves some ambiguity about whether that argument can actually be passed.

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?

With 0% schema description coverage, the Args block compensates by giving valid tone values, comma-separated platform syntax, topic examples, and image constraints. However, it documents a mode parameter that is absent from the input schema, which could confuse invocation, so it's not a perfect 5.

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?

Description opens with a specific verb-resource pair: 'Generate and publish a voice-matched post to LinkedIn, X/Twitter, or both.' This clearly distinguishes it from message/email tools and even names the target platforms, so the agent knows exactly what the tool is for.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context ('Creates posts using your voice signature for social selling', 'Builds authority and drives inbound connections') and concrete topic examples for when to use it. It doesn't explicitly compare against sibling tools like generate_and_send or send_message, but the LinkedIn/X platform scope makes the context unambiguous.

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