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 states the action ('analyze') but doesn't describe what the analysis involves, such as output format, computational intensity, or any constraints like data availability. This is a significant gap for a tool with zero annotation coverage.

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, efficient sentence with zero waste, making it appropriately sized and front-loaded. However, its brevity contributes to under-specification rather than optimal clarity, slightly reducing its effectiveness despite the concise structure.

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 (analysis task), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover behavioral aspects, parameter details, or output expectations, making it inadequate for guiding an AI agent effectively in this context.

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 description adds no meaning beyond the input schema, which has 0% schema description coverage for its 2 parameters. It doesn't explain what 'corpus_name' or 'play_name' refer to, their expected formats, or how they relate to the analysis. With low coverage, the description fails to compensate, leaving parameters largely undocumented.

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's purpose as analyzing character relationships in a play, which is clear but vague. It specifies the verb 'analyze' and resource 'character relationships in a play', but doesn't differentiate from siblings like 'find_character_across_plays' or explain what analysis entails. It avoids tautology but lacks specificity about scope or output.

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. It doesn't mention siblings like 'analyze_full_text' or 'analyze_play_structure', nor does it specify prerequisites, exclusions, or context for usage. This leaves the agent with minimal direction for tool selection.

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. It states the tool analyzes full text but doesn't describe what the analysis entails (e.g., returns insights, statistics, or summaries), any limitations (e.g., corpus availability, processing time), or side effects. This leaves key behavioral traits unspecified for a tool with no structured safety hints.

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, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be more informative by elaborating on analysis outcomes or usage context without sacrificing brevity.

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 (analysis tool with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It doesn't explain what the tool returns, how parameters are used, or behavioral aspects like error handling. For a tool that likely produces detailed outputs, this lack of context makes it inadequate for informed use.

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 the description must compensate for undocumented parameters. It mentions 'full text of a play' but doesn't explain the parameters 'corpus_name' and 'play_name', such as what values are expected or how they relate to the analysis. This adds minimal meaning beyond the schema, failing to address the coverage gap.

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 action ('analyze') and resource ('full text of a play'), specifying it includes dialogue and stage directions. It distinguishes from siblings like 'analyze_character_relations' or 'analyze_play_structure' by focusing on full text analysis, though it doesn't explicitly name alternatives. The purpose is specific but could be more precise about what 'analyze' entails.

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. It doesn't mention scenarios, prerequisites, or exclusions, such as when to choose 'analyze_play_structure' instead. Without this context, users must infer usage from tool names alone, which is insufficient for effective selection.

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 mentions analyzing 'acts, scenes, and metrics' but doesn't specify what 'metrics' entail, whether the analysis is read-only or modifies data, or what the output format might be (e.g., structured data, summary). This leaves gaps in understanding the tool's behavior, especially for a tool with parameters and no output schema.

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, consisting of a single, efficient sentence that directly states the tool's purpose. There's no unnecessary information or redundancy, making it easy to parse quickly. However, it could be slightly improved by adding a brief usage hint without sacrificing conciseness.

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 (analyzing play structure with metrics), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like whether it's a read operation, what 'metrics' includes, or how results are returned. For a tool with parameters and analytical functions, more context is needed to ensure the agent can use it 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?

The schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It doesn't add any meaning beyond what the input schema provides—it doesn't explain what 'corpus_name' or 'play_name' refer to, their expected formats, or examples. With 2 parameters and no schema descriptions, this is a significant gap, as the description fails to clarify parameter usage.

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 with a specific verb ('analyze') and resource ('structure of a play'), including what aspects it covers ('acts, scenes, and metrics'). It distinguishes itself from siblings like 'analyze_character_relations' or 'analyze_full_text' by focusing on structural analysis rather than character or textual analysis. However, it doesn't explicitly differentiate from 'compare_plays' or 'search_plays' in terms of structural vs. comparative/search functions.

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. It doesn't mention prerequisites, such as needing a specific corpus or play format, or when to choose this over siblings like 'analyze_full_text' for broader analysis or 'compare_plays' for structural comparisons. Usage is implied by the name and purpose but not explicitly stated.

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. It mentions comparing metrics and structure but doesn't specify what the tool returns (e.g., a report, scores, or visual output), whether it's read-only or has side effects, or any limitations like performance or data availability. This leaves significant gaps in understanding the tool's behavior.

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 sentence that is front-loaded and efficient, with no wasted words. It directly states the tool's function without unnecessary elaboration. However, it could be more structured by including key details, but it earns high marks for brevity and clarity within its limited scope.

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 comparing two plays with 4 parameters, no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks details on what metrics and structure are compared, the output format, and any behavioral traits. For a tool with multiple inputs and no structured support, this description is inadequate to guide effective use.

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 4 parameters with 0% description coverage, and the tool description adds no parameter semantics. It doesn't explain what 'corpus_name' or 'play_name' refer to, their expected formats, or how they relate to the comparison. With low schema coverage, the description fails to compensate, leaving parameters largely undocumented.

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 compares two plays in terms of metrics and structure, which is a clear purpose but vague. It specifies the verb 'compare' and resource 'plays', but lacks details on what specific metrics or structural aspects are compared, making it less specific. It doesn't differentiate from siblings like 'analyze_play_structure' or 'search_plays', which could involve similar analyses.

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. It doesn't mention when to choose this over sibling tools such as 'analyze_play_structure' for single-play analysis or 'find_character_across_plays' for character-focused comparisons. There are no explicit when/when-not instructions or prerequisites, leaving usage unclear.

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. It states the tool 'finds' a character, implying a read-only search operation, but doesn't specify behavioral traits like whether it returns all occurrences, pagination, error handling, or performance characteristics. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves beyond the basic action.

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, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. There's no wasted text, and it appropriately sized for the tool's apparent simplicity.

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 no annotations, no output schema, and low parameter schema coverage, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of plays, character details, or links), how results are formatted, or any limitations. For a search tool with minimal structured data, the description should provide more context to be fully helpful to an agent.

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 1 parameter with 0% description coverage, so the schema provides no semantic details. The description doesn't add any meaning beyond the schema; it doesn't explain what 'character_name' should include (e.g., full name, partial matches, case sensitivity) or provide examples. With low schema coverage, the description fails to compensate, leaving the parameter poorly documented.

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's purpose as finding a character across multiple plays in the DraCor database, which is clear but vague. It specifies the verb 'find' and resource 'character across multiple plays', but doesn't distinguish it from sibling tools like 'analyze_character_relations' or 'search_plays' that might also involve character-related operations. The purpose is understandable but lacks specificity about what 'find' entails compared to alternatives.

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. It doesn't mention prerequisites, exclusions, or compare it to sibling tools such as 'analyze_character_relations' (which might analyze character networks) or 'search_plays' (which might search for broader content). Without any context on usage scenarios, the agent must infer when this tool is appropriate based on the name 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 describes the tool as an 'advanced search' but doesn't clarify whether it's read-only, how results are returned (e.g., pagination, format), potential rate limits, or error conditions. This leaves significant gaps for an agent to understand the tool's behavior 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 well-structured and appropriately sized. It starts with a clear purpose statement, followed by a bulleted list of parameters with concise explanations. There's no wasted text, and the information is front-loaded. A slight deduction because the bulleted format, while clear, could be slightly more integrated into prose for optimal flow.

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 (9 parameters, no annotations, no output schema), the description is partially complete. It excels in parameter semantics but lacks behavioral details (e.g., output format, error handling) and usage guidelines. For a search tool with many filters, more context on result structure or limitations would help, but the parameter coverage prevents a lower score.

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 description adds substantial value beyond the input schema, which has 0% description coverage. It provides clear explanations for all 9 parameters, including examples for 'corpus_name' (e.g., 'shake', 'ger') and specific values for 'gender_filter' ('female_dominated', etc.). This fully compensates for the schema's lack of descriptions, making parameter meanings explicit and actionable.

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 'Advanced search for plays in the DraCor database with multiple filter options.' This specifies the verb ('search'), resource ('plays'), and domain ('DraCor database'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate this search tool from its siblings like 'compare_plays' or 'find_character_across_plays', which prevents a perfect score.

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. It doesn't mention sibling tools like 'find_character_across_plays' (which might overlap with the 'character_name' parameter) or 'compare_plays', nor does it specify prerequisites or optimal use cases. The agent must infer usage from the parameter list alone.

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