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PDFDashboardWithMCP

PDFDashboardWithMCP

by dakshp26
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_document

Search a specific PDF collection for content relevant to your query. Provide the collection name and a natural-language question to get matching document chunks.

Instructions

Search a document collection for chunks relevant to a query.

Args: document: Collection name as returned by list_documents. query: Natural-language question or search string.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "document": "<document>",
      "query": "<query>"
    },
    "name": "get_document"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
documentYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. 'Search' implies a read-only, non-destructive operation, but the description does not explicitly confirm this, nor does it mention any limitations or side effects. It adds no behavioral details beyond the basic operation.

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 two short sentences plus a two-item arg list. It front-loads the main action and provides all necessary param semantics in a compact, scannable format. No wasted words.

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?

For a 2-parameter search tool with an output schema, the description provides the core context: what it searches, what a valid 'document' is, and the format of the query. It could be more explicit about read-only behavior, but the search operation is inherently non-destructive. The reference to list_documents completes the workflow context.

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

Parameters5/5

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

The schema offers zero description coverage for the parameters, but the description compensates by defining 'document' as the collection name returned by list_documents and 'query' as a natural-language question or search string. This fully clarifies both parameters with useful cross-tool context.

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 opens with 'Search a document collection for chunks relevant to a query' – a specific verb ('search') plus resource ('document collection') and result type ('chunks'). It also references sibling list_documents, distinguishing this as the search-within-collection tool.

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 args section explicitly says 'Collection name as returned by list_documents,' which gives a clear prerequisite workflow. It implies when this tool should be used: after listing available documents. However, it does not explicitly state when not to use it or name alternatives beyond the implicit reference.

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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