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AdvaitR7

Firecrawl MCP Multiple Keys

by AdvaitR7

firecrawl_research_read_paper

Read-only

Retrieve the most relevant full-text passages from a specific research paper to verify if it meets a constraint, such as using a technique or reporting a benchmark score.

Instructions

Read the most relevant in-body (full-text) passages of ONE specific paper for a question. Use this to VERIFY whether a candidate actually satisfies a constraint before you include or reject it (e.g. 'does this paper actually use technique X / report a score on benchmark Y'). Returns the best-matching passages, or a notice if the paper's full text is unavailable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
paperIdYes
questionYes
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds context: it reads in-body passages, returns best-matching passages, and handles unavailability. This complements the annotations without contradiction.

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 sentences long, with the action front-loaded. Every sentence adds value: the first states the core function, the second provides purpose and expected outcomes. No redundant or vague phrasing.

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

Completeness3/5

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

The tool has three parameters, no output schema, and no enums. The description covers main behavior and one parameter (question) but omits details on 'k' and output format. With no output schema, it should at least describe the structure of returned passages. It is adequate but not fully complete.

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. It explains 'question' as a relevance driver but does not define 'paperId' or 'k.' The meaning of 'k' as the number of passages is missing, leaving ambiguity. This is a significant gap for a three-parameter tool.

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 verb 'Read' and the resource 'most relevant in-body passages of ONE specific paper for a question.' It also specifies the use case: verifying whether a candidate satisfies a constraint. This distinguishes it from sibling tools like 'firecrawl_research_search_papers' that search multiple papers.

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 explicitly says 'Use this to VERIFY whether a candidate actually satisfies a constraint before you include or reject it,' providing a clear when-to-use directive. It does not explicitly mention when not to use or compare with alternatives like 'firecrawl_research_inspect_paper,' but the positive guidance is strong and sufficient.

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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