Skip to main content
Glama

LinkedIn: Search posts

linkedin_search_posts
Read-onlyIdempotent

Search LinkedIn posts using the user's own account. Use to find a post before reading comments, checking reactions or replying. Returns post IDs required by comment/reaction tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sort_byNo
keywordsNo
account_idNoOptional Nilyo connection ID (unipile_account_id from list_connected_accounts). Omit when the user has one account for this provider. When several exist, Nilyo never guesses: list them (display name, identifier, provider user ID), choose the one the user named or ask, and pass its ID here.
date_postedNo
save_searchNo
content_typeNo
save_custom_filterNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / content_type
      Added value: +{
      +  "enum": [
      +    "VIDEOS",
      +    "IMAGES",
      +    "JOB_POSTS",
      +    "LIVE_VIDEOS",
      +    "DOCUMENTS",
      +    "COLLABORATIVE_ARTICLES"
      +  ],
      +  "type": "string"
      +}
    • addedInput schema / properties / date_posted / enum
      Added value: +[
      +  "PAST_DAY",
      +  "PAST_WEEK",
      +  "PAST_MONTH"
      +]
    • addedInput schema / properties / save_custom_filter
      Added value: +{
      +  "not": {}
      +}
    • addedInput schema / properties / save_search
      Added value: +{
      +  "not": {}
      +}
    • addedInput schema / properties / sort_by / enum
      Added value: +[
      +  "RELEVANCE",
      +  "DATE"
      +]
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuine context (it operates on the user's own account, and returns post IDs consumed by comment/reaction tools) but says nothing about pagination, result limits, or result ordering despite sort_by existing.

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?

Three short sentences, each doing distinct work: what it is, when to use it, and what it returns. The identity sentence is front-loaded and there is no filler.

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?

The chaining story (search first, then comment/react tools) is complete, but for a 7-parameter tool with 14% schema coverage and no output schema, the description omits any parameter guidance on filtering, sorting, or date scoping, which is where an agent most needs help.

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% (only account_id is documented, and it is documented in the schema, not the description). Six of seven parameters (keywords, sort_by, date_posted, content_type, save_search, save_custom_filter) get no meaning from either source, and the description does not compensate at all.

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?

States a specific verb+resource ("Search LinkedIn posts") and scopes it to the user's own account, which separates it from company-page search paths. It does not name the nearest siblings (linkedin_get_post, linkedin_list_user_posts, linkedin_resolve_my_post), so differentiation is left partly to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear chain of use: "Use to find a post before reading comments, checking reactions or replying," which routes the agent into the comment/reaction tools. No explicit when-not or exclusion cases are stated, so it stops short of full routing guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.