Skip to main content
Glama

Agent Einstein — Crypto & Market Intelligence

Robinhood Chain Whale Prints

get_robinhood_whale_prints
Read-onlyIdempotent

Individual large DEX trades on Robinhood Chain (EVM 4663) — the tokenized equities (NVDA, SPY, HIMS) and Pons memecoin flow that no mainnet whale feed carries, each with its token, side, venue and USD value. Every print is valued through its USDG or ETH leg and cross-checked, so trades priced off a freshly-created pool (which the raw chain data reports in the hundreds of millions) are excluded rather than published. WETH/USDG FX swaps are counted separately instead of dominating the tape.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows to return (1-25).

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already signal readOnly, idempotent, and non-destructive behavior; the description adds substantial non-obvious data handling context: valuation through the USDG or ETH leg, exclusion of trades priced off freshly-created pools, and separate counting of WETH/USDG FX swaps. These traits materially affect how an agent should interpret results.

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 dense but purposeful sentences: the first front-loads the resource and output contents, and the second discloses the valuation and filtering behavior. Every clause adds information needed for correct invocation or interpretation, with no filler.

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?

With no output schema, the description compensates by listing the returned fields (token, side, venue, USD value) and by explaining the exclusion and valuation rules. Combined with a fully specified optional limit parameter and safety-bearing annotations, an agent has everything needed to select and call this tool correctly.

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?

The single parameter `limit` is already fully documented in the input schema with type, default, range, and description, so schema coverage is 100%. The description adds no additional parameter-level detail, which is acceptable given the schema already carries the full burden.

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: 'Individual large DEX trades on Robinhood Chain (EVM 4663)'. It names the exact asset flows (NVDA, SPY, HIMS, Pons memecoin) and the per-print fields (token, side, venue, USD value), making it fully distinguishable from generic whale-feed siblings.

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 gives clear context: this is for Robinhood Chain trades 'that no mainnet whale feed carries', which tells an agent when to prefer this tool over mainnet whale trackers. It stops short of explicitly naming sibling tools like get_hyperliquid_whales or get_polymarket_whales, so it lacks a formal when-to-use/when-not-to-use structure.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.3/5.0
Disambiguation2/5

With 40 tools, many share overlapping domains: get_smart_money_flow vs get_smart_money_inflow, scan_launchpads vs get_launchpad_radar, track_whales vs get_hyperliquid_whales, and check_token_safety vs analyze_token_security. The detailed descriptions help, but the boundaries are not always clear, making misselection likely.

Naming Consistency2/5

The tool names employ a wide variety of verbs (get_, analyze_, scan_, track_, find_, generate_, recommend_, run_, list_, ask_, assess_, detect_) with no consistent pattern. While all use snake_case, the inconsistent verb choices and occasional deviations like forecast_chart prevent predictability.

Tool Count2/5

40 tools is well above the typical 3-15 well-scoped range and exceeds the 25+ threshold for 'too many'. While the broad 'crypto intelligence' purpose justifies some breadth, the sheer number makes the surface unwieldy and suggests a lack of focused scoping.

Completeness4/5

The tool set covers a wide range of crypto intelligence domains: market analysis, forecasting, whale tracking, yield/arbitrage, security checks, prediction markets, backtesting, and even content generation. Missing operations are minor (e.g., no direct portfolio management), but core analysis and data retrieval workflows are well represented.