OpenPapers

Search within paper

search_within_paper

Search inside a research paper's parsed content to find specific queries, returning matches with source locations for verification.

Instructions

Search parsed paper chunks and return source-located matches.

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": {
      "url": "<url>",
      "query": "<query>"
    },
    "name": "search_within_paper"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes
`limit`	No
`query`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 2, 2026

TDQS

B3/5.0

Behavior3/5

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 disclose some behavioral detail: it searches parsed chunks and returns matches with source locations. However, it does not explain whether the search is lexical or semantic, how chunking affects results, what 'source-located' means in practice, or whether the operation is side-effect free.

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 a single, compact sentence that front-loads the core action and output. There is no redundant wording, filler, or repetition of the tool name/title. It earns its place by conveying the essential behavior efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with three parameters, no output schema, and no annotations, the description is too thin to fully guide an agent. It omits how the URL is used, what the query should look like, how limit applies, what format the source-located matches take, and what happens when the paper cannot be found or parsed. Basic purpose is clear, but an agent would still have to infer several important call details.

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

Parameters2/5

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 for the lack of parameter documentation, but it does not mention url, query, or limit at all. The parameter names and constraints are somewhat self-explanatory, especially 'query' and 'limit', but the description adds no meaning about how these parameters interact with 'parsed paper chunks' or 'source-located matches'.

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?

The description clearly identifies the action ('Search') and the target resource ('parsed paper chunks'), while 'source-located matches' adds a concrete output expectation. The phrase 'within_paper' in the name and 'parsed paper chunks' in the description help distinguish it from broader search tools, though it does not explicitly name or contrast any sibling tool.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus alternatives like search_papers or vector_search. The description implies use on a specific paper via 'within paper' and 'parsed paper chunks', but it never states conditions, exclusions, or when a different tool would be more appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.