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Get LinkedIn account

linkedin_account_get
Read-onlyIdempotent

Full detail for one LinkedIn account, including its per-action daily limits and warm-up state. Configuration as it stands, not activity: for volumes sent use linkedin_account_stats, for today's headroom against the caps linkedin_account_daily_stats. Like the list, it cannot tell you whether the account has a Sales Navigator or Recruiter seat — ask the user.

Input Schema

NameRequiredDescriptionDefault
linkedAccountIdYesLinkedIn account id, from `linkedin_account_list`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds real value on top: it defines the returned scope as configuration rather than activity, and warns about a data gap (Sales Navigator / Recruiter seat) that the caller must resolve out of band. It doesn't mention error behavior for an unknown linkedAccountId, which keeps it off a 5.

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 with zero filler: scope first, negative scoping second, limitation last. Every sentence changes how an agent would select or interpret the call.

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

Completeness5/5

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

For a one-parameter read tool with full annotation coverage, the definition covers what it returns, what it explicitly does not return, which siblings to use instead, and one known blind spot. No output schema is needed given the description enumerates the relevant fields.

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 coverage is 100% and the single parameter's description already tells the agent to source the id from `linkedin_account_list`. The tool description adds nothing about the id's format or behavior for invalid ids, so it neither compensates for nor improves on the schema — baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Full detail for one LinkedIn account" states a specific verb and resource and immediately names the payload (per-action daily limits, warm-up state). It then explicitly distinguishes itself from the two nearest siblings, so an agent can route between linkedin_account_get, linkedin_account_stats and linkedin_account_daily_stats without opening a schema.

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

Usage Guidelines5/5

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

Unusually explicit routing: "Configuration as it stands, not activity" followed by two named alternatives and the condition that selects each (volumes sent → linkedin_account_stats; today's headroom against the caps → linkedin_account_daily_stats). It also states a hard limitation and the fallback (no seat info — ask the user).

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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