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southleft

LinkedIn Intelligence MCP Server

by southleft

create_draft

Create LinkedIn content drafts with titles and tags for organization and later publishing.

Instructions

Create a content draft for later publishing.

Args: content: Draft content title: Optional title for organization tags: Comma-separated tags for categorization

Returns the created draft details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
titleNo
tagsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the tool 'returns the created draft details' but doesn't disclose behavioral traits like whether this is a write operation (implied by 'create'), permission requirements, rate limits, or what happens if a draft with duplicate content is created. The description is minimal and lacks crucial operational context for a creation 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?

The description is front-loaded with the core purpose, followed by a structured Args section and return statement. It's efficient with zero wasted sentences, though the Args formatting is slightly verbose. Every sentence earns its place by clarifying parameters and output.

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 a creation tool with 3 parameters, no annotations, and an output schema (which handles return values), the description is minimally adequate. It covers purpose and parameters but lacks behavioral context like side effects or error conditions. The output schema reduces the need to explain returns, but more operational guidance would improve completeness.

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 description compensates by explaining all three parameters: 'content' as draft content, 'title' as optional for organization, and 'tags' as comma-separated for categorization. This adds meaningful semantics beyond the bare schema types, though it doesn't specify format details like tag constraints or content length limits.

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 tool creates a content draft for later publishing, specifying the verb ('create') and resource ('content draft'). It distinguishes from siblings like 'create_post' or 'create_document_post' by emphasizing it's for 'later publishing' rather than immediate posting. However, it doesn't explicitly contrast with 'update_draft' or 'publish_draft'.

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 usage context by stating 'for later publishing,' suggesting this is a preparatory step before publishing. It doesn't provide explicit when-to-use vs. alternatives like 'create_post' (immediate posting) or 'update_draft' (modifying existing drafts). No exclusions or prerequisites are mentioned.

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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