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

No annotations provided; the description explains features and customization but does not explicitly state it is read-only or disclose side effects, leaving some behavioral uncertainty.

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?

Two sentences, front-loaded with purpose and types, no wasted words, efficiently structured.

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 and rich schema, the description covers key features and usage, though it could mention limitations or prohibitions for a higher 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?

Schema covers 100% of parameters with descriptions; the description adds overall context but no new parameter-specific semantics 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 displays interactive charts, lists supported types, and distinguishes from sibling tools like display_table or display_image.

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 includes explicit usage intent ('Use this to visualize data trends...') but does not provide when-not-to-use or alternatives, though the context suggests it's for chart visualizations.

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 full burden. It discloses that the UI supports any valid URL or data URI but local file paths are auto-converted only for the listed extensions. It also mentions optional metadata parameters. Missing details like security considerations or size limits.

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 paragraph that front-loads the main purpose, but it becomes verbose with a run-on sentence about listings and formats. While all sentences add value, the structure could be more concise with better punctuation and separation.

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?

With 8 parameters, high schema description coverage, and no output schema, the description covers the tool's purpose, supported formats, parameter usage, and a key behavioral note on local file paths. It lacks error handling or constraints, but is fairly complete for a display tool.

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 baseline is 3. The description adds value by explaining the overall purpose of parameters (e.g., metadata like title, caption, dimensions, file info) and clarifying src behavior (auto-conversion for local paths). This goes beyond the schema descriptions.

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 it displays images with an interactive preview card, lists supported formats (PNG, JPG, JPEG, GIF, SVG, WebP, BMP), and establishes it as the primary tool for any visual content, implicitly differentiating from siblings that handle non-image data.

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 says 'Always use this tool whenever you need to present visual content' and lists the supported formats. It also mentions applying to listings and image operations like get/download. However, it does not mention when to use alternatives (e.g., display_chart for charts) 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.

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

With no annotations, the description carries full burden. It discloses features like interactivity and customization but doesn't explicitly state read-only behavior or absence of side effects. While likely non-destructive, more explicit transparency would help.

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 relatively concise with two sentences. It front-loads key features and purpose. Minor redundancy (e.g., 'any type of list' could be implied) but overall efficient.

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 6 parameters, no output schema, and a display tool, the description provides a solid overview of features and use cases. It covers core capabilities, though lacks explicit mention of return value (likely void). Still adequately 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?

Schema description coverage is 100%, so schema already describes each parameter. The description adds general feature context but doesn't enhance parameter meaning. Baseline 3 is appropriate.

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 it displays an interactive, customizable list with specific features like checkboxes, drag-and-drop, images, and export. It distinguishes from sibling tools by listing unique capabilities not present in display_chart or display_table.

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 says 'Perfect for displaying any type of list' and lists features, implicitly differentiating from siblings. However, it lacks explicit when-not or alternative tool guidance, though the context is clear.

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 full burden. It does not disclose behavioral traits like side effects, permissions, or limitations (e.g., rendering constraints). As a display tool, it likely has no destructive behavior, but the description fails to state this.

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?

Description is two sentences plus a tagline, with no wasted words. It front-loads the core function and efficiently covers layout, content types, and use cases.

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?

The description covers intended use and parameter-purpose mapping adequately, but given the complexity (6 params, nested objects, no output schema), it lacks details on default selection behavior, return value, or interaction with other display tools. Sufficient for a basic understanding but not fully comprehensive.

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 coverage is 100%, providing strong baselines. The description adds context about detail content types (table, image, list, text/HTML) matching the oneOf schema, and mentions layout orientation, which adds semantic value beyond raw 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 displays a master-detail view with a list and detail panel, listing specific content types (tables, images, lists, text/HTML) and use cases (browsing, comparing, navigating). It distinguishes itself from sibling display tools by being composite.

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 suggests use cases ('perfect for browsing collections...'), giving clear context. It does not provide when-not-to-use or alternative tool names, but the sibling list helps differentiate.

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 provided, so description carries full burden. Describes features but does not disclose side effects, permissions, or whether it is read-only. Lacks explicit behavioral traits beyond the listed interactivity.

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?

Two sentences covering purpose and inputs/outputs. Efficient with no wasted words, though could structure feature list more clearly.

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?

Adequate for a display tool but lacks detail on return behavior (e.g., how interactions are handled, any callbacks). With no output schema, more explanation of component behavior would help.

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 descriptions cover 50% of parameters. Description adds little beyond listing features; does not explain parameter nuances or constraints not already in 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?

Clearly states it displays an interactive table with specific features (sorting, filtering, pagination, column visibility, row selection). Distinguishes from sibling tools like display_chart or display_list by focusing on tabular data.

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?

No explicit guidance on when to use this tool versus siblings like query_table_data or display_master_detail. Does not mention prerequisites or conditions for use.

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 provided, so description must disclose behavior. It mentions node expansion/collapse, metadata display, and export functionality. However, it does not state that the tool is read-only or any side effects.

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?

Three sentences, front-loaded with purpose, no wasted words. Efficient and well-structured.

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?

Lacks description of return value or output format. No mention of error handling or performance considerations. Given no output schema, this is a gap.

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 coverage is 100%, so the description adds minimal value beyond the schema. It mentions 'metadata display' which aligns with showMetadata, but no extra context.

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?

Clearly states the tool displays an interactive tree view for hierarchical data. Lists specific use cases like file systems and org charts, distinguishing it from sibling tools like display_chart or display_table.

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 mentions when to use (hierarchical structures) but does not provide when-not-to-use or alternative tools. The sibling tools context implies alternatives, 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions server-side processing and UI-only nature, but fails to disclose authentication needs, idempotency, rate limits, or side effects. This is insufficient for a production tool.

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, consisting of just two sentences. It front-loads the core purpose and adds only essential performance context. Every word earns its place.

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 4 parameters, no output schema, and no annotations, the description is severely lacking. It does not explain return format, filter syntax, sorting behavior, error handling, or pagination boundaries. The tool cannot be reliably invoked based solely on this description.

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?

Input schema has 0% description coverage, so the description must compensate. It only vaguely hints at parameters via 'server-side sorting and filtering', but does not explain the sortBy array syntax, filter object structure, or pagination behavior. Parameter names are partially clear, but the description adds minimal value beyond 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 action ('Query table data') and key features ('server-side sorting and filtering'). It distinguishes itself from sibling display tools by explicitly noting it is a 'UI-only tool for performance with large datasets', making its purpose distinct.

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 by mentioning 'performance with large datasets', but does not explicitly state when to use vs alternatives or exclude cases. Sibling tools are display-focused, so the usage is somewhat inferred, but lacks explicit guidance.

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