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arambarnett

robinhood-chain-mcp

by arambarnett

lookup_entity

Resolve any name, ticker, or topic into a canonical entity with type, category, tags, and key attributes. Start here to get the slug for further queries.

Instructions

Resolve a name, ticker, or topic to a canonical entity in the knowledge graph. Returns entity type, category, tags, and key attributes with source provenance and confidence. Start here — other tools take the returned slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesEntity name, ticker, or topic — e.g. "Nvidia", "Donald Trump", "BTC"
Behavior4/5

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

Discloses return contents: entity type, category, tags, key attributes with provenance and confidence. No annotations exist, so description bears full weight; it covers essential behavioral aspects for a read-only lookup.

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?

Two sentences with no redundancy. First sentence states purpose and output; second provides usage guidance. Every word earns its place.

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?

Fully adequate for a simple one-parameter tool with sibling tools described. Provides entry point guidance and output overview despite no output schema.

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 description coverage is 100% with a detailed example for the single 'query' parameter. The tool description reiterates the parameter purpose but adds no new semantic detail beyond the schema.

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?

Description clearly states verb and resource: 'Resolve a name, ticker, or topic to a canonical entity in the knowledge graph.' It also distinguishes from sibling tools by noting 'other tools take the returned slug.'

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

Usage Guidelines5/5

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

Explicitly advises to 'Start here — other tools take the returned slug,' indicating this tool is the entry point for entity lookups before using siblings like entity_connections.

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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