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flin-agency

flin-linkedin-posts-mcp

by flin-agency

match_drafts_to_member_posts

Identify duplicate or similar content by comparing draft post texts to your published LinkedIn posts.

Instructions

Match draft post texts against the authenticated member's published LinkedIn posts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftsYes
page_sizeNo
published_afterNo
post_limitNo
max_matches_per_draftNo
Behavior2/5

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

No annotations provided, so the description carries full burden. It only states it operates on 'authenticated member's published posts', but does not disclose side effects, rate limits, or what happens with no matches. Minimal behavioral context beyond the basic action.

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

Conciseness2/5

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

Extremely concise (one sentence) but at the cost of omitting essential details. For a tool with 5 parameters, the description is too sparse and does not effectively front-load critical information.

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

Completeness1/5

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

With no output schema, no annotations, and a high parameter count (5), the description fails to explain return values, matching logic, or constraints. It is grossly incomplete for an AI agent to correctly invoke and interpret results.

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

Parameters1/5

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

Description does not explain any of the 5 parameters beyond the implicit mention of 'drafts'. Parameters like page_size, published_after, post_limit, and max_matches_per_draft are left entirely undefined, providing no value over the raw schema.

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 verb 'match' and the resources 'draft post texts' and 'published LinkedIn posts', which distinguishes it from sibling tools like list_member_posts or analyze_member_posts. However, it could be more specific about what 'match' entails (e.g., similarity threshold or algorithm).

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 explicit guidance on when to use this tool vs alternatives. It is implied that the user has drafts and wants to compare them to published posts, but there is no mention of prerequisites (e.g., authentication), when not to use, or references to sibling tools.

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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