Get analytics for a workspace's own published LinkedIn content. Returns engagement metrics (reactions, comments, reposts), trend vs previous period, and top-performing posts. Use fromMs/toMs as Unix timestamps (milliseconds) to define the date range.
| Name | Required | Description | Default |
|---|---|---|---|
| toMs | Yes | ||
| fromMs | Yes | ||
| workspaceId | No | Defaults to the API key's workspace |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it readOnly, idempotent, and non-destructive. The description adds what the call returns (engagement metrics, trend vs previous period, top-performing posts), which is useful 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?
Three sentences with no filler; purpose and scope are front-loaded, followed by return value, then parameter usage. Each sentence adds distinct value.
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 read-only analytics call with three parameters, the description covers purpose, date-range units, and return content. It would be slightly stronger with explicit sibling exclusion or output shape, but nothing required to make the call correctly is missing.
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 only 33%, but the description compensates by defining fromMs/toMs as Unix timestamps in milliseconds for the date range, which the schema does not provide. workspaceId is already described in the schema as defaulting to the API key's workspace.
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?
States a specific action ('Get analytics') and a well-scoped resource ('workspace's own published LinkedIn content'), and names the output categories. This distinguishes it from ad/campaign/workspace-level analytics siblings even without naming them.
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?
Gives clear context for when the tool applies: analytics on the workspace's own organic LinkedIn content. It doesn't explicitly name alternative tools or say when not to use it, but the scope is precise enough to route away from ad, campaign, and workspace metrics.
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.
Many tools share the same verb prefix (create_, list_, update_, get_) across closely related resources, so pairs like add_lead_to_external_list vs add_lead_to_sequence, create_signal_agent vs create_signal_watch, and approve_review vs approve_content_post can be confused. The descriptions are unusually detailed and cross-referenced, which mitigates but does not eliminate the ambiguity inherent in a 282-tool surface.
Virtually every tool follows the campaignstack_verb_noun snake_case pattern, which is highly predictable. Minor deviations exist: destructive operations mix remove_ and delete_ (remove_lead_list vs delete_campaign), AI generation uses both craft_ and generate_, and the seo_/search_console_ subdomains introduce a second prefix convention.
282 tools is an extreme mismatch by any reasonable standard, exceeding the 50+ threshold by more than 5x. Even for a full B2B outreach platform, this surface is far too large and would be better consolidated into higher-level operations or grouped sub-servers.
The tool surface is impressively comprehensive, covering campaigns, workflows, leads, content, ads, SEO, integrations, billing, and more with CRUD-level depth. Minor gaps remain: no single-ICP getter, no direct pause/delete for search watches, and no explicit delete for ad campaigns (only archive via update).
