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okraPDF PDF MCP server

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Describe Collection

describe_collection

Start a PDF query session by retrieving collection metadata, document list, SQLite schema, and node data model, providing the context needed to write accurate queries on the first try.

Instructions

Call this FIRST, before any execute_code or render_ui SQL. Returns collection metadata, the document list, the SQLite schema, the node data model (what a node / table / cell is, that cell values are raw strings and that row/column headers are positional sibling cells, not labels), and example queries — the context you need to write a working query on the first try.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idNoOptional document ID to probe for table serialization shape and document-specific query hints.
collection_idNoCollection ID, slug, or name. Omit to describe all documents accessible to the current API key.
Behavior4/5

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

With no annotations available, the description carries the full burden. It discloses important model semantics (cell values are raw strings; headers are positional sibling cells, not labels) and the full scope of returned context. It doesn't explicitly state whether the operation is read-only or has side effects, but the nature of the tool implies safety, leaving only a minor transparency gap.

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 critical instruction ('Call this FIRST'), then efficiently lists return contents and concludes with the value proposition. Every clause earns its place, and the length is appropriate for the complexity.

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 tool with no required parameters and no output schema, the description is remarkably complete: it enumerates the return types, explains the tricky node data model, and states the overall purpose. The agent has all needed context to invoke it correctly without further exploration.

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?

The input schema already provides 100% coverage for both parameters, describing `document_id` and `collection_id` with usage details. The tool description itself adds no additional parameter-level guidance, so the baseline of 3 applies.

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 what the tool does: 'Returns collection metadata, the document list, the SQLite schema, the node data model... and example queries.' It uses a specific verb ('returns') and names concrete resources. It distinguishes from siblings by explicitly positioning it as a prerequisite to execute_code and render_ui, making its role unique.

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

Usage Guidelines4/5

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

The description gives explicit timing with 'Call this FIRST, before any execute_code or render_ui SQL,' which tells the agent when to use it relative to key siblings. However, it does not provide when-not-to-use scenarios or alternatives beyond those two tools, so it stops short of a 5.

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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