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whale-insights

by com.cryptowhaleinsights

golden_alerts_snapshot

Golden Alerts snapshot — latest market intelligence alerts (public, MCP-compatible) — Returns the latest snapshot of CryptoWhaleInsights Golden Alerts — up to 27 high-signal market alerts refreshed every 5 minutes by the platform's cron job. Each alert represents a confluence of whale on-chain activity, volume momentum, and Fear & Greed context. This endpoint reads directly from the in-process cache (no new AI query triggered per request). Pro-only fields (raw confidence score, internal factors, price targets, exit signals) are intentionally omitted; severity is mapped to low/medium/high for public consumption. Alert types: accumulation | fear_buy | smart_money_loading | volume_breakout | whale_convergence. Severity mapping: high (confidence ≥70%), medium (45–69%), low (<45%). Response: { alerts[], total, refreshedAt (ISO-8601 or null if cache empty), updatedAt }. Each alert: id, title, type, severity, tokens (string[]), chains (string[]), summary, aiInsight, analystId (string | null), createdAt. No authentic

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description fully discloses behavioral traits: cache-based read, periodic refresh (5 min), omission of pro fields, severity mapping logic, and response shape. The cut-off 'No authentic' likely indicates no authentication, but is incomplete.

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 moderately concise, front-loading purpose and caching behavior. Every sentence adds value, though the length could be slightly trimmed. Well-structured with clear sections (types, severity, response).

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 output schema, the description comprehensively details the response format, including alert fields, severity mapping, and refresh timing. It addresses edge cases (null refreshedAt when cache empty). Covers all necessary context for a snapshot tool with no parameters.

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?

The tool has zero parameters, so the baseline is 4. The description adds value by detailing the output structure, alert fields, and severity mapping, going beyond what the empty schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the latest snapshot of Golden Alerts, specifying sources (whale activity, volume momentum, Fear & Greed), alert types, and severity mapping. It distinguishes from history/monthly siblings by virtue of being a 'snapshot', though not explicitly naming alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context (cache read, no AI query, public) but does not instruct when to use this tool vs alternatives like golden_alerts_history or golden_alerts_monthly. No when-not to use or exclusion criteria.

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.

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