list_draftsList the user's unpublished LinkedIn post drafts. Use it to review the content pipeline or find a draft to edit, schedule, or publish.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max drafts to return. Defaults to 25, capped at 100. | |
| cursor | No | Pagination token from a previous response; omit for the first page. |
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes |
Changes observed during successful MCP inspections.
Output schema / properties / items / items / properties / updated_atAdded value: +{
+ "$ref": "#/properties/items/items/properties/created_at"
+}Output schema / properties / items / items / properties / media / items / properties / titleAdded value: +{
+ "description": "Document title shown on LinkedIn. Only set for documents.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already establish a read-only, idempotent, closed-world operation. The description adds useful result-scope context—only the user's unpublished drafts—but does not disclose further behavioral traits such as ordering or empty-result behavior.
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 short sentences front-load the exact operation and scope, then provide practical usage contexts. There is no redundant or unnecessary wording.
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 two-parameter paginated read with an output schema and safety annotations, the description supplies the essential scope and selection context needed for correct invocation. Explicit sibling routing would be a refinement rather than a material omission.
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?
Both parameters are fully documented in the schema, including limit's default and cap and cursor's pagination usage. The description adds no parameter meaning beyond that coverage, so the high-coverage baseline of 3 applies.
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 specifies the verb, resource, and scope: listing the user's unpublished LinkedIn post drafts. That scope distinguishes it from siblings such as list_posts, list_comment_drafts, and get_draft without requiring schema inspection.
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?
It gives concrete selection contexts: reviewing the content pipeline or finding a draft to edit, schedule, or publish. It does not explicitly route agents to get_draft for a known draft or to sibling list tools for other resources.
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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