Digche Icons

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 reveals that candidates are found and ranked and that context improves match quality. It does not disclose ranking criteria, failure behavior, or output format, but for a read-only lookup the core behavior is reasonably clear.

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 sentences with no filler. The core purpose is front-loaded, and the usage hint about UI context is packed into the second sentence without redundancy.

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 tool has five parameters, no output schema, and no annotations, so the description could do more. It leaves the return shape and ranking criteria unspecified and does not distinguish itself from recommend_icons. Still, the schema covers parameter semantics well enough for a basic call.

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 60%, so the description partially compensates. It adds meaning to context (functional UI context, English or Persian) and clarifies that sourceIcon/sourceLibrary refer to icons from common icon libraries. It does not add value for limit or preferredStyle beyond what the schema already provides.

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 ('find and rank'), a clear resource ('Digche replacements'), and the source scope ('an icon from Lucide, Heroicons, Material Symbols, Font Awesome, or another library'). It is distinct from a generic icon search, though it does not explicitly contrast with the sibling recommend_icons tool.

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 gives a practical usage directive: 'Include the UI context for a more useful match' and notes the context may be English or Persian. However, it does not explain when to choose this tool over search_icons or recommend_icons, nor when it should not be used.

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 behavioral burden. It explains the meaningful difference between 'svg' and 'jsx' output and calls the result 'validated'. It does not cover fallback or error behavior, but the core behavior is transparent.

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 concise sentences, front-loaded with the main purpose, then style guidance, then format guidance. Every sentence earns its place and there is no redundancy with the schema.

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?

Covers the required slug, style preference, and format semantics, which is sufficient for most calls. The undocumented allowFallback parameter and lack of output schema details prevent a perfect completeness rating.

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. It adds meaning for style and format, and indirectly for slug. However, allowFallback is never explained, leaving a notable gap for one of the four 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 states a specific action ('Retrieve') on a specific resource ('validated SVG variant after selecting a Digche slug'). This clearly distinguishes the tool from siblings like search_icons, preview_icons, and recommend_icons.

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?

Provides practical guidance on when to prefer Linear style and when to use jsx vs svg format. It does not explicitly name alternatives or exclusion conditions, but the retrieval-by-slug context makes the intended use 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?

With no annotations, the description carries the burden of disclosing behavior. It adds meaningful context by stating it lists 'every published' category (scope) and includes 'icon count and available styles' (content). The phrase 'Call this once' also hints at low cost, which is helpful. It does not explicitly say it is read-only, but 'list' strongly implies that.

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 sentences with no fluff. The first sentence delivers the core functionality, and the second sentence provides usage guidance. Every part earns its place, and it is front-loaded with the key action.

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 tool is simple (0 params, no output schema). The description covers what it returns (categories with counts and styles) and when to use it. It could explicitly state that it returns a list/array, but 'List every...' implicitly conveys that. It is complete enough for an agent to invoke correctly.

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 has zero parameters, so the description cannot add parameter-level meaning. The schema already covers everything (empty properties). The baseline for 0 parameters is 4, and the description appropriately does not invent unnecessary parameter details.

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 lists every published Digche category, including icon count and available styles. It uses a specific verb ('List') and resource ('Digche category'), and it distinguishes itself from sibling tools like search_icons by focusing on catalog vocabulary rather than searching.

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 gives a clear 'when to use': 'Call this once to learn the catalog vocabulary before filtering searches by category.' It implies this is a one-time setup step and not for ongoing filtering, though it does not explicitly name alternatives or state 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 the full burden of behavioral disclosure. It states that the tool renders a single image for comparison, but it does not mention read-only nature, output format details, or how conflicting inputs (slugs + query) are handled. Some behavior is implied (e.g., search+preview) but not fully elaborated.

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 compact sentences, front-loaded with purpose and then usage. Every word contributes, with no redundant restating of the tool name or schema details.

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 tool with 5 optional params and no output schema, the description covers core behavior and both usage modes. It omits some details like default handling when neither slugs nor query are supplied, and it doesn't explicitly describe the returned image format, but the schema fills some gaps (defaults, limits).

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 60% of parameters (limit, query, slugs), and the description adds relational meaning: slugs come from a previous tool call, query is an alternative for one-step search+preview. However, style and theme have no description and are left only as enum labels, relying on implicit understanding.

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 the specific verb 'Render' with a clear resource ('candidate Digche icons') and the intended outcome ('compare them before choosing'). It distinguishes the tool from siblings like search_icons (which searches/returns metadata) and get_icon_svg (which returns a single SVG) by emphasizing a single composite image for comparison.

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 defines two usage modes: pass slugs from an earlier tool call, or use a query to search and preview in one step. This clearly indicates when to use the tool, though it does not name alternative tools or state exclusions (e.g., not for fetching SVGs).

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 behavioral disclosure burden. It adds useful behavioral facts beyond the schema: the 20-slot cap, English/Persian input support, and the dependence on an overall task for disambiguation. It does not explicitly confirm there are no side effects, but the described behavior is a read-only recommendation and nothing hints at mutation.

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 compact sentences, each earning its place: core capability, one usage hint, and routing to the appropriate alternative. No repetition of schema or title.

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 five parameters, no annotations, and no output schema, the description plus input schema cover the main operational contours: inputs, modes, styles, and batch limits. Minor edge behaviors such as what happens when a slot has no match or the list exceeds 20 are not addressed, but the core is adequately 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?

The schema already documents most parameters (80% coverage), so the baseline is 3. The description adds value by explaining the 20-slot batch limit, bilingual slot names, and the instruction to provide task context so ambiguous slots resolve correctly—details absent from 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 names a specific action ('Pick a coherent Digche icon set'), a precise target ('up to 20 named UI slots'), and a distinguishing batch property ('in one call'). This clearly separates it from single-icon sibling tools like search_icons or get_icon_svg.

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 explicitly tells the agent when to prefer this tool: 'Use this instead of one search per icon when laying out a screen.' It also gives a concrete precondition for better results: 'Give the overall task so ambiguous slot names resolve correctly.'

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 discloses how queries behave (bilingual, Persian aliases) and what is returned (paste-ready summary and preview image). While it doesn't explicitly state 'read-only,' the word 'Search' and the output description strongly imply a non-destructive query operation.

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 three tight sentences with no fluff: purpose, usage guidance, and return summary. Every sentence contributes actionable information, and the most important facts are front-loaded.

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 4-parameter search tool with no output schema, the description covers the essential call path: what to search, how to phrase the query, and what to expect in the response. Minor gaps remain around limit/style/category usage, but these are partially self-documenting in the schema and the tool is simple enough that the description is nearly sufficient.

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 useful meaning to the query parameter by listing matching fields and language handling. However, it doesn't explain the limit clamp, the style enum values, or the category slug pattern, and with 50% schema coverage the added value only partially compensates for the undocumented 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 clearly identifies the action ('Search published Digche icons') and enumerates search dimensions (name, alias, use case, tag, category, functional meaning). It positions the tool as the entry point for icon selection with 'Use this before choosing a UI icon,' though it doesn't explicitly name sibling tools or say what it is not.

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 gives explicit timing guidance: use this before choosing a UI icon. It also provides an actionable language rule—pass the user's own Persian wording instead of translating it first. It doesn't discuss when to prefer a sibling tool, but the context is clear for the common case.

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