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AlpineDataWorks Intelligence Server

by com.alpinedataworks

Crypto Fear & Greed Index

adw.adw_587
Read-only

Returns a 0-100 crypto market sentiment score (alternative.me Fear & Greed composite of volatility, momentum/volume, social media, BTC dominance, and search trends) with classification label, 7-day change, 30-day average, and 30-day daily history. Call when the user asks about crypto market mood, fear vs. greed, sentiment extremes, or contrarian signals, or when timing crypto entries, exits, or rebalancing around emotional peaks and troughs. Updates: daily.

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

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, but the description adds valuable behavioral context: 'Updates: daily', the composition of the score (volatility, momentum/volume, social media, BTC dominance, search trends), and the inclusion of historical series in the default output. This goes beyond the annotations without contradicting them.

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 three concise sentences: one for output details, one for usage guidance, one for update frequency. Every sentence carries substantive information with no filler. It is front-loaded with the key 'Returns a 0-100...' statement.

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?

The tool is simple (one optional parameter, no output schema), but the description comprehensively explains the return values (score, label, 7-day change, 30-day average, 30-day history), the data source, the update schedule, and when to use it. The 'days' parameter behavior is documented in the schema, so no gaps remain.

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?

Input schema covers 100% of the single optional 'days' parameter, so the baseline is 3. The description adds nuance by revealing the default snapshot includes a 30-day daily history, which helps clarify the meaning of the 'days' parameter (i.e., it overrides the default with a longer history). This is useful beyond the schema's description.

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 crypto market sentiment score with specific output fields (classification label, 7-day change, 30-day average, 30-day daily history). It specifies the resource (alternative.me Fear & Greed composite) and the verb 'Returns', making it distinct from any sibling tools despite their opaque numeric names.

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 explicitly provides multiple 'Call when' scenarios: crypto market mood, fear vs. greed, sentiment extremes, contrarian signals, and timing crypto entries/exits. While it does not mention alternatives or 'when not to use', the usage guidance is specific and actionable for an AI agent.

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