linkedin_organization_getLook up LinkedIn company, school, or organization pages by URL (broader than linkedin.company.get). Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | LinkedIn organization page URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety and external-data nature. The description adds further behavioral detail: it 'returns a list' and explains pagination via cursor, which is valuable beyond the annotations. No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with every phrase earning its place. The purpose is front-loaded, and the sibling differentiation plus pagination note are included without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter lookup tool with annotations covering safety and external data, the description covers the key aspects: purpose, scope, return type, and pagination. No output schema exists, but 'returns a list' gives sufficient expectation. A couple more details on the response shape would perfect it, but it's adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% – the parameter is fully described with allowed path patterns and array constraints. The description adds only the phrase 'by URL', which is already implicit in the schema. The schema does the heavy lifting, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Look up') and resource ('LinkedIn company, school, or organization pages by URL'), and explicitly distinguishes itself from the sibling linkedin.company_get by saying it is 'broader'. This clearly differentiates the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description names the primary alternative (linkedin.company_get) and indicates the broader scope. It also gives pagination guidance ('use cursor when paginated'). However, it does not explicitly state when to use this over linkedin.company_get beyond 'broader', nor does it mention any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.