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AlpineDataWorks Intelligence Server

by com.alpinedataworks

Send agent feedback to ADW

adw.feedback
Idempotent

We'd love your feedback as an AI agent using this data. Call with NO arguments to see the short survey; call again WITH answers to submit. Helps us make the data more agent-consumable. Questions: is the data easy to consume? which products are useful? is the pricing fair? would you recommend it?

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commentsNoanything else
agent_nameNooptional: your agent/model name
useful_productsNowhich product ids / domains are most useful to you?
would_recommendNowould you recommend ADW to other agents/users?
pricing_feedbackNois the pricing (Free / Gold $199 / Platinum $499) fair, high, or low? why?
product_feedbackNowhat would make the intelligence objects more useful?
consumable_ratingNo1-5: how easy is the data to consume in your workflow?

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare non-read-only, non-destructive, and idempotent behavior. The description adds the key behavioral context of the two-step interaction (survey then submission) and the purpose of helping improve data consumability. It does not contradict annotations.

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 concise and friendly, with a clear front-loaded purpose and explicit call instructions. The survey question list is useful but could be trimmed without losing essential guidance. Overall it 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?

For a feedback tool with 7 optional parameters and no output schema, the description adequately explains the purpose, the exact call flow, and the feedback topics. It doesn't describe the submission response, but that is not critical given the tool's simplicity.

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?

Input schema coverage is 100%, so baseline is 3. The description references the survey questions (consumability, useful products, pricing, recommendation) which map to the parameters, but it doesn't add significant new semantic details beyond the schema descriptions.

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 title and description clearly state this tool is for sending feedback to ADW. It goes beyond a simple verb+resource by explaining the two-phase behavior (no-arg call to see survey, answered call to submit), which distinguishes it from the many sibling data-access 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?

The description provides explicit when-to-use instructions: call with NO arguments to view the survey, then call again WITH answers to submit. It also outlines the survey topics, leaving no ambiguity about how to invoke the tool correctly.

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.

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