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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it specifies that credentials are stored in ~/.spotify-mcp-tokens.json along with session tokens, mentions automatic browser opening for OAuth, and outlines the flow for handling errors and manual authorization. However, it lacks details on rate limits, error handling beyond initial setup, or authentication state persistence.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the purpose, followed by a structured, numbered list for the workflow. Each sentence serves a clear purpose, such as guiding through authentication steps and noting storage details. However, it could be slightly more concise by integrating the storage note into the workflow or reducing redundancy in step explanations.

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

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

Given the complexity of an authentication tool with multiple actions and no annotations or output schema, the description is largely complete. It covers the authentication flow, storage behavior, and usage scenarios. However, it lacks information on output formats or error responses, which could hinder an AI agent's ability to handle post-invocation logic effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal parameter semantics beyond the schema, mainly by contextualizing 'accion' values within the recommended workflow (e.g., 'verificar=comprobar estado (USAR PRIMERO)'). This aligns with the baseline score of 3 when schema coverage is high.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool manages Spotify authentication, which is a clear purpose, but it's somewhat vague about the specific actions. It doesn't explicitly distinguish this authentication tool from sibling tools like spotifyInfo, spotifyLibrary, or spotifyPlayer, which likely perform different functions after authentication. The description focuses on workflow rather than a concise statement of what the tool does.

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

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

The description provides explicit, step-by-step guidance on when to use different actions based on scenarios (e.g., if credentials aren't configured, use 'configurar'; after configuring, use 'ejecutar'; if manual authorization is needed, use 'urlAuth'). It includes alternatives and prerequisites, such as obtaining credentials from Spotify Developer Dashboard, making it highly 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.

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so effectively. It reveals important behavioral traits including the need for an active device for certain actions (nowPlaying/state/queue), the workflow for playing music (search first, then use spotifyPlayer), and device checking procedures. The only gap is lack of information about rate limits or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized but not optimally structured. While it contains valuable information, it uses a bulleted list format that mixes usage guidelines with behavioral information, making it less front-loaded than ideal. Every sentence earns its place, but the organization could be more logical.

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

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

Given the tool's complexity (8 parameters, multiple action types) and lack of both annotations and output schema, the description provides substantial context. It covers usage scenarios, prerequisites, and behavioral constraints effectively. The main gap is the absence of information about return values or response formats, which would be helpful given the lack of output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3. The description doesn't add significant parameter semantics beyond what's already in the schema descriptions, though it does provide context about how the 'accion' parameter maps to specific use cases. No additional syntax or format details are provided beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as searching and obtaining information from Spotify, which is a specific verb+resource combination. It distinguishes from sibling tools like spotifyPlayer by focusing on information retrieval rather than playback control, though the distinction could be more explicit about being purely informational versus interactive.

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

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

The description provides excellent usage guidelines with explicit examples for common scenarios like playing music, checking devices, and monitoring playback. It clearly distinguishes when to use this tool versus spotifyPlayer and includes important prerequisites about device requirements for certain actions like nowPlaying/state/queue.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions actions like 'save', 'createPlaylist', etc., it doesn't describe behavioral traits such as authentication requirements, rate limits, error handling, or what happens on mutations (e.g., whether deletions are permanent). The focus is on workflows rather than behavioral transparency, leaving significant gaps for an AI agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a brief purpose statement, bullet-pointed common flows, and a note, making it easy to scan. However, it includes some redundancy (e.g., repeating how to get IDs) and could be more front-loaded with a clearer tool definition. Overall, it's efficient but not perfectly concise.

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

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

Given the complexity (7 parameters, no annotations, no output schema), the description is partially complete. It covers usage workflows and parameter sourcing well, but lacks details on behavioral aspects (e.g., side effects, errors) and doesn't explain return values. This is adequate for basic use but leaves gaps for an AI agent to fully understand the tool's behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so parameters are well-documented in the schema itself. The description adds some value by explaining how to obtain IDs (e.g., from spotifyInfo) and listing common actions, but it doesn't provide additional semantic details beyond what the schema already covers. This meets the baseline of 3 given the high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Gestiona biblioteca y playlists del usuario' which translates to 'Manages user library and playlists', providing a general purpose. However, it's vague about the specific actions and doesn't clearly distinguish this tool from its siblings (spotifyAuth, spotifyInfo, spotifyPlayer) beyond mentioning them in usage examples. The description focuses more on workflows than on defining the tool's core function.

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

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

The description provides explicit usage guidelines through 'FLUJOS COMUNES' (common flows) and a 'NOTA' section. It details when to use this tool versus alternatives like spotifyInfo for obtaining IDs, and specifies workflows for common tasks (e.g., saving current song, creating playlists). This gives clear context on when and how to invoke the tool relative to siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It excels by detailing error-handling scenarios (e.g., 'No hay dispositivo activo', 'Premium requerido'), recovery steps (using spotifyInfo, transfer, openApp), and user interactions (e.g., 'Pide al usuario que reproduzca algo manualmente'). This goes far beyond basic functionality.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is overly verbose and poorly structured, mixing purpose, error-handling, and workflows in a dense paragraph. It lacks front-loading of core functionality, and many sentences could be condensed or moved to a separate guidelines section, reducing clarity.

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

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

Given the complexity of a playback control tool with no annotations and no output schema, the description is highly complete. It covers purpose, usage scenarios, error recovery, and integration with sibling tools, providing all necessary context for an agent to operate effectively despite missing structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add significant meaning beyond the schema, though it implies usage patterns (e.g., using 'uri' or 'tipo+id' for play). Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'Controla reproduccion de Spotify' (controls Spotify playback), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like spotifyInfo or spotifyLibrary, though the focus on playback control implies a distinction.

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

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

The description provides extensive usage guidelines, including explicit error-handling workflows (e.g., 'Si error "No hay dispositivo activo"'), recommended flows ('FLUJO RECOMENDADO cuando no reproduce'), and references to sibling tools (spotifyInfo for search and devices). It clearly indicates when and how to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.