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rh_liquidity_map

Liquidity map for a tokenized stock: aggregates every indexed Robinhood Chain pool and breaks down where the liquidity lives venue by venue (Uniswap/Pleiades/Rialto/Arcus...), with each venue's liquidity, 24h volume, price, and liquidity share. Send { ticker }. Route large orders to the deepest venues and avoid thin pools. [x402 paid tool — price $0.005; POST /api/rh/liquidity-map]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock/ETF ticker, e.g. NVDA

TDQS

A4.2/5.0
Behavior4/5

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

Given no annotations, the description carries full burden. It discloses that the tool aggregates indexed pools, returns venue-level data, and is a paid tool with pricing and endpoint. It doesn't mention auth or rate limits, but the key behaviors are transparent.

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?

Three sentences, each purposeful: first defines the tool, second provides usage guidance, third adds pricing and endpoint info. Front-loaded and no unnecessary 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 tool with one parameter and no output schema, the description explains the output structure (venue breakdown) and gives context on when to use. It is sufficiently complete for an AI agent to understand its role among siblings.

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% with description for 'ticker'. The description adds minimal extra beyond the schema, reinforcing that it's a stock/ETF ticker. The baseline of 3 is appropriate as the schema already provides adequate meaning.

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 tool provides a liquidity map for a tokenized stock, breaking down liquidity by venue (Uniswap, Pleiades, Rialto, Arcus) with details like liquidity, volume, price, and share. It specifically mentions the ticker parameter, making its purpose unambiguous.

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 instructs to send a ticker and provides actionable advice: 'Route large orders to the deepest venues and avoid thin pools.' It does not explicitly state when not to use or alternatives, but the guidance is clear and practical.

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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TDQS

A3.5/5.0
Disambiguation4/5

Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.

Tool Count2/5

With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.

Completeness4/5

The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.