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CaseyRo

Readwise MCP HTTP Server

by CaseyRo

export_highlights

Export reading highlights in bulk from Readwise with optional filters for specific dates or books, using pagination for large datasets.

Instructions

Bulk export highlights, optionally filtered by date or specific books.

Use cursor from a previous response to paginate through large exports. Each result includes the full highlight with book metadata attached.

This uses the export endpoint — use it for bulk data retrieval, not for interactive queries. For interactive use, prefer search_highlights or list_highlights instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
updated_afterNo
book_idsNo
cursorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes
next_cursorNo
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by disclosing key behaviors: pagination support via cursor, inclusion of book metadata in results, and the tool's nature as an export endpoint for bulk operations. It doesn't cover all possible behaviors like rate limits or auth needs, but provides substantial context.

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?

The description is front-loaded with the core purpose, followed by usage details and alternatives in three concise sentences. Every sentence adds value without redundancy, making it efficient and well-structured.

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?

Given the tool's complexity (bulk export with pagination), no annotations, and an output schema present, the description is largely complete. It covers purpose, usage, key behaviors, and parameter semantics, though it could add more on error handling or response structure beyond metadata mention.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the purpose of parameters: filtering by date ('updated_after' implied) or specific books ('book_ids'), and pagination via cursor. However, it doesn't detail parameter formats or constraints, leaving some gaps.

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?

The description clearly states the specific action ('bulk export highlights') and resource ('highlights'), distinguishing it from siblings like search_highlights or list_highlights by emphasizing bulk data retrieval. It explicitly mentions filtering capabilities by date or books, adding specificity.

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?

The description provides explicit guidance on when to use this tool ('for bulk data retrieval') and when not to ('not for interactive queries'), naming alternatives like search_highlights and list_highlights for interactive use. This clearly differentiates it from sibling tools.

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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