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whale-insights

by com.cryptowhaleinsights

analysts_top

Get the highest win-rate analyst right now — one analyst with win rate, avg return, last 3 signals (min 5 resolved trades required) — Returns the single analyst with the highest win rate among those with at least 5 resolved signals, plus their last 3 recent signals (using the free 7-day window). Useful for AI agents that want to surface the best-performing signal source without iterating over all 10 analysts. Returns { analyst: null } when no analyst yet has 5+ resolved signals. Analyst IDs map to: chain_hawk=ChainHawk (BTC), whale_watch=WhaleWatch (multi-chain), alpha_scout=AlphaScout (emerging tokens), defi_pulse=DeFiPulse (DeFi/stables), quant_edge=QuantEdge (risk/convergence). winRate is a fraction (0.71 = 71%); avgReturn is percentage points (12.3 = +12.3%). Cached ~10min.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior5/5

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

Despite no annotations, the description fully discloses behavior: caching (~10min), return format with null case, mapping of analyst IDs to names, and field semantics (winRate as fraction, avgReturn as percentage). No contradictions.

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 thorough but not overly verbose. It front-loads key information and each sentence adds value. Slightly longer than necessary but still efficient.

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?

Given no parameters and no output schema, the description provides complete context: conditions, return structure, caching, and field interpretations. No gaps.

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?

No parameters exist, so baseline is 4. The description adds no param info, which is appropriate since schema coverage is 100% (empty object).

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 returns the single analyst with the highest win rate, including specific fields (win rate, avg return, last 3 signals) and conditions (min 5 resolved trades). It distinguishes from sibling tools like 'analysts' by focusing on top performance, making it easy for an agent to select.

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?

Explicitly identifies its use case: 'Useful for AI agents that want to surface the best-performing signal source without iterating over all 10 analysts.' It provides clear when-to-use guidance but lacks explicit when-not-to or alternative tool mentions.

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but there are a few pairs with overlapping boundaries (e.g., analysts_signals vs analysts_signals_all, whale_movements vs whale_movements_summary) that could cause minor confusion.

Naming Consistency4/5

Naming is predominantly snake_case and descriptive, with minor inconsistencies in plural/singular forms (e.g., 'analysts' vs 'analyst_archive'). Overall pattern is stable.

Tool Count2/5

With 55 tools, the server is quite heavy. While the scope is broad, many tools are history/monthly variants that could be combined, making the count feel inflated beyond what is ideal for a single server.

Completeness4/5

The tool set covers a wide range of crypto analytics domains (analysts, arbitrage, funding, whales, sentiment, etc.). Minor gaps exist (e.g., no direct token price endpoint), but overall it's a comprehensive surface.

Resources