ColorSnapAI Color Seasons

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

The read-only annotation already covers safety, but the description adds useful behavior: it returns a rough estimate, a runner-up when close, the palette, and a link to a more accurate service. It appropriately warns about limited accuracy, though it does not describe error behavior for invalid hex input.

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 two tight sentences, front-loading what the tool does and then covering the return shape and accuracy caveat. Every sentence adds value without repetition.

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?

For a simple three-parameter read-only computation with rich schema descriptions, the definition is complete enough to call correctly. Since there is no output schema, the description usefully explains the returned season, palette, runner-up, and link.

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 for all three required hex parameters, so the schema already explains their meaning and format. The description adds contextual framing like natural hair and cheek/iris locations, but no substantial detail 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 states a specific verb and resource: estimating someone's color season from hex hair, skin, and eye colors. It also distinguishes the operation from the sibling palette/list tools by making the input and estimation behavior explicit.

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?

It clearly frames when the tool applies: when you have hex colors for natural hair, cheek skin, and iris. It also points to a more accurate photo-based alternative, though it does not explicitly compare against the sibling tools.

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?

Annotations already establish readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing the exact shape of the result (counts of recommended and avoided colors, metals, description text, and an external link), which matters because there is no output schema. It does not mention whether the returned link is promotional or how the palette is ordered.

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 definition is a single front-loaded sentence that enumerates the payload, but the trailing clause about 'ColorSnapAI's free photo analysis' reads as promotional rather than operational and does not help the agent invoke the tool.

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 no output schema, the description carries the burden of describing return values and does so thoroughly, listing each component of the payload. The only gap is that it never clarifies its relationship to the two sibling tools, which would be the remaining piece an agent needs for correct selection.

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% and the single parameter is an enum of exactly the 12 season names, so the schema fully documents the input. The description adds nothing about season naming beyond what the enum already provides, which is the correct baseline for a fully documented single parameter.

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 uses a clear verb ('Returns') with a specific resource ('a season's palette') and enumerates the payload (12 colors with names and hex, 4 colors to avoid, best metals, a description). It doesn't name its siblings estimate_color_season or list_color_seasons, so the agent must infer the boundary between 'look up a known season' and 'estimate my season' on its own.

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 usage is only implied: you call it with a season you already know. There is no explicit statement of when to use this versus estimate_color_season (photo-based analysis) or list_color_seasons (enumeration), and no prerequisites or exclusions are given.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and the closed nature of the domain are covered. The description adds that each entry carries a one-line description, which is useful shape information, but says nothing about ordering, formatting, or size of the result.

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 short sentences with the content summary first and the usage hint second. Every clause earns its place and nothing is padded.

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?

For a trivial no-parameter read with no output schema, the description is nearly sufficient: it tells the agent it will get twelve named seasons each with a one-liner. The only missing piece is how to relate the result to the sibling tools when narrowing a season.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. Nothing in the description misleads about 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?

States a specific verb and resource ('Lists the 12 seasons of seasonal color analysis') plus the shape of the content (a one-line description of each), which is materially more than the title. It is distinguishable from get_season_palette and estimate_color_season by being a reference list, though it never names those siblings explicitly.

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?

It offers usage context ('use it to explain the system or help someone narrow down their season') but no exclusions or routing rules. The 'narrow down their season' phrasing actually overlaps with what estimate_color_season presumably does, leaving the agent to guess which tool to prefer for that goal.

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