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AlpineDataWorks Intelligence Server

by com.alpinedataworks

Crypto Whale-Flow Pressure

adw.adw_110
Read-only

Returns a 0-100 Bitcoin whale-flow pressure score (weekly composite z-score of large-holder accumulation vs. distribution; above 65 signals accumulation, below 40 distribution) with trend, percentile, top_drivers, confidence, and source_lineage. Call when the user asks about BTC whales, large holders, smart money, on-chain flows, or whether whales are buying or selling, or when timing BTC allocation shifts, crypto rebalancing, or funding-rate position adjustments. Updates: weekly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoOptional: return a daily HISTORY series of the last N days (up to 5 years of real archived data) instead of the current snapshot. History requires Gold tier; without it, the current snapshot is returned.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description adds valuable context: it discloses the update frequency ('Updates: weekly'), the score scale and interpretation, and indirectly mentions the Gold tier requirement via the schema. It does not describe return format or rate limits, but for a read-only tool this is adequate.

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 two sentences with no waste. It front-loads the core mechanism (score range, interpretation), then lists outputs and usage triggers. Every sentence earns its place.

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 simple read-only nature, the tool is well covered. The description lists output fields and usage context, while the schema covers the optional parameter and tier requirement. It lacks an output schema, but the description names the fields explicitly, making it complete enough for an agent.

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 description coverage is 100% for the single optional 'days' parameter, and the schema itself provides detailed semantics (returns history series up to 5 years, requires Gold tier). The description adds no parameter-specific meaning beyond the schema, so the baseline 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 the tool returns a 0-100 Bitcoin whale-flow pressure score, with detailed interpretation (above 65 accumulation, below 40 distribution) and a list of output fields. This specific verb+resource+scope fully distinguishes it from sibling tools.

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

Usage Guidelines5/5

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

Explicit usage guidance is provided: 'Call when the user asks about BTC whales, large holders, smart money, on-chain flows, or whether whales are buying or selling, or when timing BTC allocation shifts, crypto rebalancing, or funding-rate position adjustments.' This gives clear triggers and context for selecting this tool.

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

B3.3/5.0
Disambiguation1/5

With 318 tools named adw.adw_###, agents cannot tell them apart without reading full descriptions. Multiple tools cover the same domain (e.g., at least three USD strength scores: adw_055, adw_250, adw_580; four supply-chain stress scores: adw_009, adw_019, adw_020, adw_547), making misselection highly likely.

Naming Consistency3/5

The vast majority follow a consistent numeric ID pattern (adw.adw_###), but a small set breaks this with descriptive snake_case names (adw.catalog, adw.sample, adw.county_cancer, etc.). The numeric IDs are predictable but convey no semantic meaning, mixing with the few named tools and creating moderate inconsistency.

Tool Count1/5

318 tools is far beyond any reasonable scope for an intelligence server; even the largest sophisticated APIs rarely exceed 50. This extreme count suggests poor curation and will overwhelm agents with choice, making efficient tool selection impractical.

Completeness3/5

The server covers an extremely broad range of domains (crypto, macro, supply chain, healthcare, climate, county demographics), and includes discovery tools like adw.catalog and adw.sample. However, the surface is redundant and not systematically complete—many overlapping indices exist while other potentially valuable operations (e.g., raw data export, historical trend queries) are missing, leaving moderate gaps.

Resources