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Glama

get_episode_full

Get full episode data in one call — details, summary, quotes and asset mentions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
episode_idYesEpisode ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the primary behavior (retrieval of specific episode components) and adds value by explaining what 'full' includes. However, it omits any mention of authentication, response format, error behavior, or potential rate limits, leaving gaps for an agent.

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, well-structured sentence that front-loads the core action ('Get full episode data in one call') and directly lists contents. Every word is purposeful, with no fluff or repetition.

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?

The description is sufficient for a simple get tool with a single parameter: it states what the tool does and what data it returns. No output schema exists, but the listed components give a clear expectation. Minor gaps remain (e.g., whether transcript is included), but overall it is well-complete for the tool's complexity.

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?

The input schema already provides 100% coverage with a clear description for episode_id ('Episode ID'). The tool description adds no additional parameter-level detail, so it meets the baseline of 3 for high schema coverage.

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: 'Get full episode data in one call' with a specific list of included data (details, summary, quotes, asset mentions). It distinguishes itself from sibling tools like get_episode_details and get_episode_quotes by aggregating multiple data types.

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 phrase 'in one call' suggests using this tool when you need all the listed data at once, implicitly contrasting with the need for multiple calls to other tools. It provides clear context but does not explicitly mention alternatives or when not to use it.

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