Skip to main content
Glama
horizonbymuneeb

linkedin-mcp-pro

build_digest

Builds a digest of LinkedIn feed activity, summarizing top posts, mentions, keyword alerts, trending content, and warnings for a specified lookback period.

Instructions

Build a digest of the last N hours of feed activity (top posts, mentions, keyword alerts, trending, warnings).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lookback_hoursNo
Behavior2/5

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

No annotations are provided, and the description does not disclose side effects (e.g., whether the digest is stored or just computed), return value, authentication requirements, or rate limits. 'Build' is ambiguous about state changes.

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 concise: a single sentence that front-loads the main action and lists included content. No redundant information, though it could be slightly more structured.

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

Completeness2/5

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

Given the lack of output schema and annotations, the description should provide more context about the output format, how to access the digest, and whether it modifies state. It is incomplete for an agent to fully understand tool behavior.

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?

The only parameter (lookback_hours) is not mentioned in the description. Schema description coverage is 0%, so the description should explain the parameter, but it does not. While the parameter is self-explanatory, the description adds no semantic value beyond the 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 tool builds a digest of feed activity over a time window, listing included categories (top posts, mentions, etc.). However, it does not differentiate from the sibling tool 'get_digest_markdown', which may serve a similar purpose.

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 guidance on when to use this tool versus alternatives like get_feed, poll_feed, or get_digest_markdown. The description implies a summarization use case but lacks explicit context.

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/horizonbymuneeb/linkedin-mcp-pro'

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