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Get today's usage and limits

get_usage
Read-only

How many direct LinkedIn actions (invitations, messages, comments, reactions, posts, searches and the rest) your LinkedIn account has used today, the daily limit for each, and when the count resets. invitations holds the longer counts for invitations: whether the account counts as paid or free, the last 7 days against the weekly limit, on a free account the invitations with a note in the last 30 days, and how long a note can be. Read-only.

Input Schema

NameRequiredDescriptionDefault
connectionIdNoWhich of your LinkedIn accounts to act from (its id from list_linkedin_accounts). Omit to use your first live one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/openWorldHint/destructiveHint, so the restated 'Read-only.' is low value. The description earns credit by adding real behavioral context the annotations lack: that the `invitations` field varies by paid vs free account tier, spans 7-day and 30-day windows, and carries the maximum note length.

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?

Roughly two sentences with no filler; the core answer (what is counted, the limit, the reset) is front-loaded before the deeper `invitations` detail. The second sentence is clause-heavy and reads as a run-on, which slightly hurts scannability.

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

Completeness4/5

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

There is no output schema, so the description carries the return-shape burden and largely meets it, describing per-action counts, limits, and reset timing plus the special `invitations` payload. It does not describe the container format or ordering of the per-action results, which is a minor residual gap.

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 description coverage is 100% and the single connectionId parameter is fully documented in the schema, including the fallback behavior for omitted values. The description adds nothing about connectionId, so the baseline of 3 applies.

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 names a specific resource (today's direct-action usage, per-action daily limits, reset timing) and enumerates exactly which action types are covered, so an agent knows precisely what it retrieves. It stops short of naming or ruling out the closest sibling, get_inmail_credits, which is the one plausible confusion point for a quota tool.

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?

There is no explicit when-to-use, when-not-to-use, or alternative-tool guidance. Usage is only implied: because the tool reports remaining daily quota and reset time, an agent can infer it is meant to be called before performing actions such as send_invitation or comment_on_post.

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

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