PaletteGet

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 conveys the output shape (CSS custom properties with semantic names) but says nothing about read-only status, required auth, whether an invalid slug errors or falls back, or per-platform output differences — a significant gap for an unannotated 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?

A single compact sentence that front-loads the resource and the key output characteristic. Nothing is padded, though it is arguably undersized given the undocumented platform parameter.

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 partially compensates by characterizing the return value (CSS custom properties, semantic names, paste-ready). But it omits any explanation of the platform parameter's effect and any routing guidance among the three sibling palette tools, leaving the definition only minimally viable.

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 only 50%: 'slug' is briefly glossed as '配色 slug' while 'platform' has an enum but no description at all. The tool description never mentions either parameter, so it does not compensate for the documentation gap — notably, nothing explains what selecting 'app' vs 'web' vs 'miniapp' does to the output.

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: retrieving CSS custom properties for a color scheme, with the useful detail that they are directly pasteable and semantically named. It is clear what the tool returns, though it never distinguishes itself from the sibling get_palette, leaving the agent to infer that this one is the CSS-format export variant.

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 parenthetical '(可直接粘进项目)' implies a usage context (export-ready CSS for embedding in a project), which hints at when to prefer this over get_palette. However, there is no explicit when-to-use statement, no when-not-to-use, and no reference to any sibling 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, the description carries the full behavioral burden. It does disclose the shape of the returned content (roles, contrast, human pairing advice), which is genuinely useful given there is no output schema, but it says nothing about read-only semantics, permission needs, or behavior on a nonexistent slug.

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?

A single front-loaded sentence with a colon-delimited payload list; nothing is padded. It is efficient, though the brevity leaves little room for the routing and behavioral context an unannotated tool needs.

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 two-parameter read tool with no annotations and no output schema, the description covers what comes back but omits error behavior for an unknown slug and any guidance on the platform parameter's fallback. It is adequate but not 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 both slug and the platform enum are already documented in the schema, making 3 the baseline. The description adds only the implied notion of retrieving complete data for a palette, not any new syntax or format detail for the 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 names a specific verb (取, retrieve) and resource (某一套配色, a single palette) and enumerates the payload (role color values, contrast, pairing suggestions), so it is clearly not list_palettes or suggest_palette. It never names those siblings, though, so the differentiation is inferable rather than 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?

Usage is only implied: the required slug signals that this is the lookup-by-identifier path, distinct from listing or generating. There is no statement of when to prefer it over get_css_variables (e.g. raw variables vs. curated palette data) or what to do when a slug is unknown.

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?

Since there are no annotations, the description must carry the behavioral burden. It significantly adds value by detailing exactly what fields the agent can expect to receive in the response (name, slug, primary color, scene, and tag), providing vital structural context.

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 highly concise, using a single sentence to convey the tool's function, available filters, and the specific set of data fields returned. There is zero wasted information.

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 filtering/listing tool, the description is completely adequate. It defines the available parameters and clearly states the structure of the expected output data fields, leaving no critical operational gaps for the 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?

Schema description coverage is 100%, setting a baseline of 3. The description reinforces the filtering functionality (platform and tag) and the default scope ('if not filled, all three are listed'), but it does not add critical semantic meaning beyond what the existing schema parameters already define.

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 ('list') and specifies the resource ('color palettes in the library'). Crucially, it defines the operation as a listing and filtering task, distinguishing it from tools like get_palette or suggest_palette.

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 clearly outlines the mechanisms available for selecting data (filtering by platform and tag). This defines the scope of usage, implying its use for broad data retrieval rather than focused retrieval, though it does not explicitly state 'when not to use get_palette'.

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 the full burden. It does disclose two useful behavioral facts: queries work in Chinese or English, and results explain what each match hit. It says nothing about determinism, whether results are cached palettes or generated, or any rate/limit behaviour beyond the schema's default.

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?

A single compact sentence with the core action front-loaded, followed by examples and one return-value note. No filler, though the examples and the '命中' note could be tightened.

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 read-only suggestion tool with no output schema and no annotations, the description should at least clarify the platform parameter's effect and what a returned suggestion contains. It covers the return semantics loosely ('会说明每个结果命中了什么') but leaves the platform dimension and result shape under-specified.

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 67%: query and limit are self-documented, but the platform enum (app/web/miniapp) is unexplained in both schema and description. The description does add real value by stating query accepts Chinese or English space-separated keywords, which goes beyond the schema's example.

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?

Names a specific verb (推荐) and resource (配色) plus the input modality (自然语言关键词), with two concrete examples that make the intent unambiguous. It does not explicitly contrast itself with the read-oriented siblings (get_palette, list_palettes, get_css_variables), so an agent must infer the keyword-vs-lookup distinction.

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 examples (「护眼的深色记账 App」) imply when this tool fits — when the user describes a mood or product rather than naming a palette — but there is no explicit 'use this instead of X when...' routing. No prerequisites or exclusions are stated.

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