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wshobson

MaverickMCP

research_comprehensive_research

Conduct in-depth financial research on any topic using web search and AI analysis, with adjustable scope and persona for tailored insights.

Instructions

Perform comprehensive research on any financial topic using web search and AI analysis.

Enhanced features:

  • Generous timeout (basic: 120s, standard: 240s, comprehensive: 360s, exhaustive: 600s)

  • Intelligent source optimization

  • Parallel LLM processing

  • Progressive token budgeting

  • Partial results on timeout

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesResearch query or topic
personaNoInvestor persona (conservative, moderate, aggressive, day_trader)moderate
research_scopeNoResearch scope (basic, standard, comprehensive, exhaustive)standard
max_sourcesNoMaximum sources to analyze (1-50)
timeframeNoTime frame for search (1d, 1w, 1m, 3m)1m

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description partially covers behavior by mentioning timeouts, parallel processing, and partial results. However, it lacks details on side effects like API costs, rate limits, or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and uses a clear bullet list for features. It is somewhat verbose but still efficient, with no unnecessary fluff.

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?

Given complexity (5 parameters, output schema exists), the description covers overall purpose and key features but lacks usage guidance and edge-case behavior. 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.

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description mentions research scope and persona but adds no meaningful detail beyond the schema descriptions. It does not explain parameter interactions or format expectations.

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 states it performs comprehensive research on financial topics using web search and AI analysis. It lists enhanced features that distinguish it from siblings, but could be more explicit about its scope compared to other research tools.

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?

The description provides no explicit guidance on when to use this tool versus alternatives. It lists features but does not specify contexts or conditions for using different research scopes (basic, standard, etc.).

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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