Skip to main content
Glama
ejwhite7

@b2b-saas-inc/olli-mcp-server

reply_to_linkedin_conversation

Send an automated reply to a LinkedIn messaging conversation. Provide the workspace, conversation ID, and message text.

Instructions

Send a reply in a LinkedIn messaging conversation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_idYesWorkspace slug or UUID
conversation_idYesLinkedIn conversation ID
messageYesReply message text
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only states the action without disclosing behavioral traits such as how the reply is sent, authentication requirements, or any side effects. The minimal description fails to inform about the outcome or safety profile.

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 a single sentence with no redundant information, achieving maximum conciseness. It is front-loaded and immediately clear.

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 the tool has no output schema and no annotations, the description should provide more context on return values or outcomes. It only describes the basic action, omitting what happens after sending (e.g., confirmation or response format). This is adequate but leaves gaps.

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 coverage is 100% with each parameter described. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage. No extra constraints or formatting details are provided.

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 'Send a reply in a LinkedIn messaging conversation' uses a specific verb ('reply') and identifies the resource ('LinkedIn messaging conversation'), making the tool's purpose unmistakable. It clearly distinguishes from sibling tools like 'list_linkedin_conversations' and 'reply_to_ticket'.

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 for sending replies but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ejwhite7/olli-social-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server