colorapi

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

No annotations are provided, so the description carries the full burden. It mentions the conversion outputs (hex, HSL, HSV, CMYK, color name) but does not disclose behavioral traits such as error handling for invalid inputs, performance characteristics, or any limitations (e.g., precision of conversions). This leaves gaps in understanding how the tool behaves beyond its basic function.

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 (conversion) and lists all outputs without unnecessary details. Every word contributes to understanding the tool's function, making it appropriately sized 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?

Given the tool's moderate complexity (conversion with multiple outputs), no annotations, and no output schema, the description is somewhat complete but lacks details on return values, error cases, or behavioral context. It covers what the tool does but not how it operates or what results to expect, leaving room for improvement in completeness.

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%, with clear documentation of r, g, b parameters as RGB channels with range 0-255. The description adds no additional parameter semantics beyond what the schema provides, such as format details or constraints. Baseline 3 is appropriate since the schema adequately covers parameter information.

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 specific action ('convert an RGB color') and the comprehensive outcome ('to all other color formats... and get its closest color name'). It distinguishes from sibling tools like 'generate_scheme' and 'identify_color' by focusing on format conversion rather than scheme generation or color identification.

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 when RGB input is available and conversion to multiple formats is needed, but it does not explicitly state when to use this tool versus alternatives like 'generate_scheme' or 'identify_color'. No exclusions or prerequisites are mentioned, leaving usage context somewhat vague.

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 states the tool returns 'a set of harmonious colors' but doesn't describe the return format (e.g., array of hex values), potential errors (e.g., invalid hex input), or any side effects. For a tool with zero annotation coverage, this leaves significant behavioral gaps, though it does mention the output is based on the chosen mode.

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, well-structured sentence that efficiently conveys the core functionality: generating a color scheme from a seed hex with mode-based harmony. It's front-loaded with the main purpose and avoids unnecessary details, making it highly concise with zero waste.

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 and no output schema, the description is incomplete. It doesn't explain what the returned 'set of harmonious colors' looks like (e.g., format, structure), potential constraints, or error handling. For a tool with 3 parameters and no structured output information, the description should provide more context to be fully helpful.

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 three parameters (hex, mode, count) with details like format, enums, and defaults. The description adds minimal value beyond the schema by implying the hex is a seed and mode influences harmony, but doesn't provide additional syntax or usage context. This 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.

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 a color scheme from a seed hex color' specifies the verb (generate) and resource (color scheme). It distinguishes from sibling tools like 'convert_color' and 'identify_color' by focusing on scheme generation rather than conversion or identification. However, it doesn't explicitly differentiate from potential overlapping functionality, keeping it at a 4 rather than a 5.

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 like 'convert_color' or 'identify_color'. It mentions 'based on the chosen mode' but doesn't explain when to choose different modes or what contexts suit this tool. There are no explicit when/when-not statements or prerequisites, resulting in minimal usage guidance.

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 the return values (color name, format representations, contrast info), which is helpful, but it doesn't describe error handling (e.g., invalid hex values), performance characteristics, rate limits, or authentication needs. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 and front-loaded, consisting of just two sentences that directly state the tool's purpose and output. Every sentence earns its place by providing essential information without redundancy or fluff, making it highly efficient and easy to parse.

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 low complexity (one parameter, no annotations, no output schema), the description is somewhat complete but has gaps. It explains what the tool does and what it returns, which is adequate for basic use. However, without annotations or an output schema, it lacks details on error cases, behavioral traits, and exact return structure, making it minimally viable 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 description coverage is 100%, so the schema already documents the 'hex' parameter thoroughly. The description adds marginal value by reinforcing the purpose ('identify a color by its hex value'), but it doesn't provide additional syntax, format details, or constraints beyond what the schema specifies. With only one parameter and high schema coverage, a baseline of 3 is appropriate, but the description's clarity elevates it slightly.

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 specific action ('identify a color by its hex value') and the resource (color information). It distinguishes from sibling tools like 'convert_color' (which likely transforms between formats) and 'generate_scheme' (which likely creates color palettes) by focusing on identification and comprehensive representation extraction rather than conversion or generation.

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 when you have a hex value and need detailed color information, but it doesn't explicitly state when to use this tool versus alternatives like 'convert_color' or 'generate_scheme'. There's no guidance on prerequisites, exclusions, or specific scenarios where this tool is preferred over others, leaving usage context somewhat ambiguous.

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