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rh_oracle_deviation

Chainlink oracle health for a tokenized stock on Robinhood Chain: reads the live onchain Chainlink feed (latestRoundData) and compares it to the DEX spot and the real equity price, with staleness (age vs heartbeat) and deviation %. Send { ticker }. Catch stale or dislocated oracles before they trigger bad liquidations. Reads onchain via Robinhood Chain RPC. [x402 paid tool — price $0.05; POST /api/rh/oracle-deviation]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock/ETF ticker with a Chainlink feed, e.g. NVDA, TSLA, SPY

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It explains the tool reads onchain data (read-only), compares prices, and outputs staleness and deviation. It also discloses it's a paid tool ($0.05) and the endpoint. This gives sufficient behavioral context, though it doesn't detail error handling or missing feed scenarios.

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 front-loaded with the core purpose, then details the comparison, use case, and implementation. Every sentence adds value without redundancy. It is concise yet comprehensive for a single-parameter tool.

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?

Given the tool has one parameter and no output schema, the description adequately covers the key outputs (staleness, deviation) and provides implementation context (onchain read, paid tool). It lacks explicit output format but sufficient for an agent to understand what the tool returns.

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 the ticker parameter description already stating 'Stock/ETF ticker with a Chainlink feed'. The tool description adds examples (NVDA, TSLA, SPY) and context about oracle health, but this does not significantly extend beyond the schema. Baseline of 3 is appropriate.

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 it reads Chainlink oracle health and compares to DEX spot and real equity price, with staleness and deviation. It uses specific verbs like 'reads' and 'compares', and identifies the resource as 'oracle health for a tokenized stock'. This distinguishes it from sibling tools like rh_dislocation or rh_arb that focus on different aspects.

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 provides a clear use case: 'Catch stale or dislocated oracles before they trigger bad liquidations.' It instructs the user to 'Send { ticker }' and gives context about reading onchain via Robinhood Chain RPC. However, it does not explicitly state when not to use this tool or suggest alternative tools for similar needs.

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.