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 correctly indicates this is a read operation ('Check') but doesn't specify what the health check entails (e.g., response time, uptime, specific endpoints), whether it requires authentication, rate limits, or what constitutes 'healthy' status. The description provides basic behavioral context but lacks operational details.

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 a single, focused sentence that states the tool's purpose without any unnecessary words. It's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place, and there's no redundancy or structural issues.

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 simplicity (zero parameters, health check operation) and the presence of an output schema, the description is reasonably complete. It states what the tool does at a high level, though it could benefit from slightly more detail about what 'health status' includes. The output schema will handle return value documentation, so the description doesn't need to cover that aspect.

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 tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't mention parameters since none exist, and it doesn't need to compensate for any schema gaps. The description focuses correctly on the tool's purpose rather than parameter details.

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 verb ('Check') and resource ('health status of the MusicMCP.AI API service'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like check_credit_balance, but the specific focus on API health provides inherent distinction. The description avoids tautology by specifying what is being checked beyond just the tool name.

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 implies usage context (monitoring API health) but doesn't provide explicit guidance on when to use this tool versus alternatives like check_credit_balance or the song generation tools. No when-not-to-use scenarios or prerequisites are mentioned. The implied context is reasonable but lacks explicit comparison or exclusion criteria.

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 full burden for behavioral disclosure. 'Check' implies a read-only operation, but the description doesn't specify authentication requirements, rate limits, response format, or whether this affects system state. For a financial tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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 extremely concise - a single four-word sentence that communicates the core purpose without unnecessary elaboration. While perhaps too minimal for optimal clarity, it's efficiently structured with zero wasted words.

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 has zero parameters, 100% schema coverage, and an output schema exists, the description's minimalism is somewhat acceptable. However, for a financial balance check with no annotations, the description should ideally specify what type of credits, for which account/system, and basic behavioral context to be truly complete.

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 tool has zero parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for matching the schema's completeness regarding inputs.

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 'Check your credit balance' clearly states the action (check) and resource (credit balance), making the basic purpose understandable. However, it doesn't differentiate this tool from its siblings (health check, song generation tools) or specify what system/account's credit balance is being checked, leaving room for ambiguity.

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 no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, frequency recommendations, or comparison to sibling tools like check_api_health. The agent must infer usage context entirely from the tool name and description alone.

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 effectively describes key traits: it's a generative tool that makes API calls to MusicMCP.AI, incurs costs (5 credits per generation), creates 2 songs per generation, and handles multilingual inputs. However, it doesn't mention rate limits, error conditions, or authentication needs.

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 well-structured and appropriately sized. It starts with the core purpose, followed by usage guidelines, example, cost warning, language note, and parameter explanations. Every sentence adds value with no redundant information, making it easy to scan and understand.

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 (generative, cost-incurring, multilingual) and the presence of an output schema (which handles return values), the description is complete enough. It covers purpose, usage, behavioral traits, cost implications, language handling, and parameter semantics, providing comprehensive context for effective tool selection and invocation.

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 0% schema description coverage, the description must compensate. It provides meaningful context for all parameters: title is required and part of detailed song information, lyric is optional and not required when instrumental is True, tags specify music style, and instrumental indicates whether the song is lyrics-free. The description adds value beyond the bare schema by explaining relationships between parameters.

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 generates songs based on detailed song information, specifying the verb 'generate' and resource 'songs'. It distinguishes from sibling tools like generate_prompt_song by emphasizing 'detailed song information' and 'custom mode', making its specific purpose evident.

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 explicitly states 'Use when users provide detailed song information including song name, complete lyrics, and style' and provides a clear example. It also includes a cost warning that advises 'Only use when explicitly requested by the user', offering strong guidance on when to use and when to avoid this tool.

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 full burden and does well: discloses cost implications (5 credits per generation, API call to MusicMCP.AI), specifies output quantity (2 songs per generation), mentions language handling (pass prompt in user's input language), and describes return format (song information including download URLs). Could improve by mentioning rate limits or error conditions.

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?

Well-structured with clear sections: purpose statement, usage guidelines, examples, warnings, language note, parameter explanations, and return description. Every sentence adds value with zero wasted text. Front-loaded with core functionality.

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 3 parameters with 0% schema coverage and no annotations, the description provides comprehensive context: clear purpose, usage guidelines, behavioral details (cost, output quantity, language handling), parameter semantics, and mentions return format. With output schema existing, it appropriately doesn't detail return values further.

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 0%, so description must compensate. It provides good semantic context for all 3 parameters: 'prompt' as 'Song theme or emotional description, 1-1200 characters', 'instrumental' as 'Whether instrumental only (no lyrics)', and 'style' as 'Music style (e.g., "ambient", "pop", "rock"), default None'. Adds character limits and examples beyond basic 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: 'Generate songs based on simple text descriptions' with AI generating title, lyrics, style, etc. It distinguishes from sibling 'generate_custom_song' by specifying this is for 'simple text descriptions' versus presumably more detailed specifications.

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?

Explicitly states when to use: 'Use when users only provide simple song themes or emotional descriptions without detailed specifications.' Provides three concrete example inputs and warns against unnecessary use due to cost implications. Clearly differentiates from more detailed song generation alternatives.

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