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0xrhXBT — Robinhood Chain Intelligence

check_token_risk

Pre-trade risk readout for a Robinhood Chain token by symbol or 0x address — designed to be called BEFORE placing a trade elsewhere (e.g. via robinhood agentic trading). Returns observed data only, never a buy/sell recommendation: liquidity/volume/holders, rug-guard status, launch-radar assessment when available (riskGate pass|watch|fail, opportunity 0-100, data confidence, risk flags, paid-promotion flag), named safety checks (sellability, lp burn, concentration, snipers, contract verification, mint authority, tax, age — each pass|fail|unknown with a Blockscout proof link; unknown means not assessed, never clean), and the estimated one-shot exit price impact for your trade size. Unknown values are null, never fabricated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trade_size_usdNointended trade size in USD for exit-impact estimate (default 2000)
symbol_or_addressYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so comprehensively. It states 'Returns observed data only, never a buy/sell recommendation,' 'Unknown values are null, never fabricated,' and clarifies that 'unknown means not assessed, never clean.' It also details the exact data fields and their semantics, providing strong transparency about what the tool does and does not do.

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 a single dense paragraph that packs a lot of information but remains logically structured: purpose first, then output details, then handling of unknown values. It is efficient, though it could be broken into bullet points for readability. It is not overly verbose and every sentence adds value.

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 lack of an output schema and annotations, the description is thorough in explaining what data is returned, the meaning of each field, and the behavior for unknown values. It covers the main aspects an agent would need to call the tool correctly. Minor gaps remain, such as error handling for invalid symbols, but these are not critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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

Schema coverage is only 50% (trade_size_usd has a description, symbol_or_address does not). The description compensates by explaining what each parameter is for: 'by symbol or 0x address' for symbol_or_address and 'for exit-impact estimate' for trade_size_usd. This adds meaning beyond the schema, though it could be more explicit about the default value of trade_size_usd.

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 opens with a specific verb-resource pair ('Pre-trade risk readout for a Robinhood Chain token by symbol or 0x address'), which clearly states what the tool does. It also differentiates itself from siblings by emphasizing its pre-trade safety assessment role, contrasting with tools like get_token or get_launch_radar.

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?

It explicitly states when to use the tool: 'designed to be called BEFORE placing a trade elsewhere (e.g. via robinhood agentic trading).' This gives clear usage context. However, it does not mention when NOT to use it or name alternative tools, so it falls short of a 5.

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

A3.7/5.0
Disambiguation5/5

Every tool targets a distinct slice of Robinhood Chain intelligence: token data, premiums, perp markets, stablecoin flows, corporate actions, risk checks, and sentiment. Even overlapping areas (e.g., get_token vs. search_tokens, get_stock_premiums vs. get_stock_multipliers) are clearly separated by purpose. No two tools appear to duplicate each other's core function.

Naming Consistency3/5

The tool names mix conventions: most are verb-led (get_, search_, check_), but several are noun phrases (chain_composition, perps_markets, stablecoin_flows). Within the get_ group the pattern is consistent, but across the full set the mixing of prefixes and bare nouns makes the naming less predictable. Still, each name is descriptive enough to infer its role at a glance.

Tool Count2/5

With 26 tools, the set exceeds the 25-tool threshold for 'too many'. While the domain is broad (covering tokens, perps, stablecoins, corporate actions, flows, and narratives), the sheer number risks over engineering and agent confusion. Some tools could be grouped (e.g., perps_funding and perps_markets might be one, get_token and get_token_candles might share). The scope feels stretched.

Completeness4/5

The surface covers a comprehensive array of Robinhood Chain data: token details, market premiums, perp funding, stablecoin flows, settlement graphs, corporate actions, and risk assessment. Minor gaps exist (e.g., no direct wallet transaction history, no governance queries), but for the stated purpose of 'chain intelligence' the coverage is robust and includes both live and historical reads.

Resources