AudioAlpha

get_ticker_featured_quotes

Get featured podcast quotes for a specific crypto asset on a given date, with α-sentiment scores (0-10 scale), ranked by selection score.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	No	Date in YYYY-MM-DD format. Omit for latest.
`ticker`	Yes	Asset ticker symbol. IMPORTANT: all crypto tickers MUST be suffixed with "-USD" — e.g. BTC-USD, ETH-USD, SOL-USD. Bare symbols like "BTC" will not match and will return an empty / 404 response.
`version_info`	No	When true, include version metadata in the response: both version_num (the revision number) and version_label (a human-readable label like "eod_utc" for the initial end-of-day build, or "revised" when a later-indexed podcast triggered a regeneration). When false (the default), neither field is included. Note: the snapshot generation "status" field is ALWAYS returned regardless of this flag.
`snapshot_type`	No	Asset universe to draw the snapshot from. Currently only "crypto" is available; "tradfi" is reserved for a future release. Defaults to "crypto".	crypto
`version_number`	No	Which revision of the snapshot to return. Each snapshot date can be re-generated multiple times (version 1, 2, 3, …). Use -1 (the default) to always get the latest authoritative version (is_latest = true). If you request a specific version that does not exist for the given date + snapshot_type, the latest version is returned instead.

TDQS

A3.7/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that results are ranked by selection score and include α-sentiment scores on a 0-10 scale. However, it does not explain response format, error behavior, or data freshness, which could be important.

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 a single sentence that effectively communicates the core purpose without filler. It is front-loaded with the action and resource, making it easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema and annotations, the description does not fully explain response structure or edge cases. However, the schema covers parameter specifics, and the description gives a reasonable overview. It could mention pagination or limit behavior, but it is adequate for basic use.

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?

All five parameters have thorough schema descriptions with examples and defaults. The tool description adds no extra parameter meaning; schema coverage is 100%, so the baseline score of 3 applies.

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's function: retrieving featured podcast quotes for a specific crypto asset on a given date, with α-sentiment scores and ranking. It distinguishes itself from sibling tools like get_market_featured_quotes by specifying 'specific crypto asset'.

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

Usage Guidelines3/5

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

The description implies usage for a single ticker via 'specific crypto asset' but does not explicitly contrast with alternatives such as get_market_featured_quotes or get_episode_quotes. There is no when-not-to-use guidance.

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

A3.9/5.0

Disambiguation5/5

Every tool targets a distinct resource and data aspect: episode details, quotes, transcript, summary, market snapshots, ticker history, user feeds, etc. Even the 'full' composite variants are clearly described as one-call conveniences that bundle granular data, so there is no real ambiguity about which tool to use.

Naming Consistency5/5

All 23 tools follow a consistent 'get_<entity>_<detail>' pattern using lowercase snake_case. This uniformity makes the tool names predictable and mentally indexed, with no mixing of verb styles or naming conventions.

Tool Count3/5

With 23 tools, the server sits in the 'heavy' range (16–25) and feels a bit bloated. The breadth of resources justifies many endpoints, but several composite 'full' versions and overlapping history functions inflate the count and could be consolidated without losing capability.

Completeness4/5

The read-only surface covers core workflows well: episode-level detail, podcast discovery, market-wide snapshots/history/themes, ticker-specific data/leaderboards, and user personalization. Minor gaps include no way to enumerate all supported tickers or podcasts beyond search, and no direct episode list by date without going through the market endpoint.

Resources

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