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Reach MCP — LinkedIn for AI agents

list_jobs

Read-onlyIdempotent

Jobs of this user, newest first, without their items. Filter by account or status (scheduled, running, paused, completed, cancelled).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of jobs; default 50.
statusNoOnly jobs in this status.
account_idNoReach id of the LinkedIn account to act on, from list_accounts.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
itemsNoJobs, newest first.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description still adds real value beyond them by disclosing the sort order (newest first) and the fact that job items are excluded from the response, which shapes what the agent can expect.

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?

Two tight sentences with no filler; the ordering and payload-exclusion facts are front-loaded, followed immediately by the filtering options.

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?

An output schema exists, so return values need not be explained, and the annotations cover the safety profile. The description supplies the sort order and the missing-items caveat, leaving only pagination/default behavior (covered by the schema) unaddressed.

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?

With 100% schema description coverage, the schema already documents limit, status, and account_id, and the enum lists the status values. The description's enumeration of statuses is largely redundant and it adds no format or semantics beyond the schema, so baseline 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?

States the resource (jobs), its scope (of this user), ordering (newest first), and a payload characteristic (without their items), which is enough to distinguish it from get_job at a glance. It does not explicitly name get_job or the create/pause/cancel job siblings as alternatives, so it stops short of full sibling differentiation.

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?

"Filter by account or status" implies the retrieval context but never says when to choose this over get_job for a single job or the other job-management tools. Usage is inferable but not stated, which is the definition of minimum-viable guidance.

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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