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Preview a campaign LinkedIn invite

preview_campaign_linkedin_invite

Render the LinkedIn connection note a campaign would send (AI from rules/tone, or fixed text with placeholders), with its length vs the 200-char limit. Pass campaign_id to use saved settings. No sending, no credits.

Input Schema

NameRequiredDescriptionDefault
modeNo
toneNo
promptNo
sampleNoSample recipient used for the preview (defaults to a demo contact).
agent_idNo
exact_textNo
campaign_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden; it discloses the key safety properties that nothing is sent and no credits are used, and mentions the 200-character limit. It does not cover permissions, whether saved campaign settings are only read, rate limits, or what exactly the rendered output contains beyond length.

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?

The description is three compact sentences, front-loaded with the core rendering behavior, then the character-limit detail, then campaign_id usage and the no-send/no-credit guarantee. Every sentence adds relevant information without repetition.

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?

For a 7-parameter tool with no output schema and low schema description coverage, the description explains the core preview behavior and output length comparison but leaves several parameters and return details unexplained. It is adequate for understanding the main purpose but incomplete for fully confident invocation.

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

Parameters2/5

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

Schema description coverage is only 14%, so the description must compensate, but it only clarifies campaign_id and loosely maps to mode/tone via 'AI from rules/tone, or fixed text with placeholders.' It says nothing about prompt, sample, agent_id, exact_text, or their meanings and constraints, leaving most of the 7 parameters undocumented.

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 names a specific verb and resource: render the LinkedIn connection note a campaign would send, covering both AI and fixed-text modes. This is clearly distinct from sibling preview tools for followups, emails, or non-campaign LinkedIn invites.

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?

It gives useful context ('Pass campaign_id to use saved settings') and clarifies 'No sending, no credits,' which helps an agent understand this is a preview operation. However, it does not explicitly name when to use this instead of preview_linkedin_invite, preview_campaign_linkedin_followup, or other preview siblings.

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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