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Recommend a Digche set for a screen

recommend_icons

Pick a coherent Digche icon set for up to 20 named UI slots in one call. Give the overall task so ambiguous slot names resolve correctly. Use this instead of one search per icon when laying out a screen.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNoWhat the screen is, for example: sidebar for a billing dashboard.
slotsYesUI slots to fill, for example ["profile", "billing", "logout"].
limitPerSlotNo1 to 5 candidates per slot.
responseModeNoplan returns slugs only; assets adds the SVG for each top pick.plan
preferredStyleNoLinear

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description itself must disclose behavior. It reveals that the tool recommends a coherent set, supports up to 20 slots in one call, and uses the task context to resolve ambiguity. However, it doesn't disclose the output format (e.g., slugs vs. SVG) or any side effects, though the responseMode parameter covers the format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no filler. It front-loads the main action, then provides guidance on the task parameter, and ends with the usage comparison to search_icons.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (5 params, no output schema, no annotations), the description covers the core use case and distinguishes it from siblings. The main omission is explicit mention of responseMode (plan vs assets), but the parameter description in the schema covers that. Overall, it's sufficiently complete 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.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents most parameters (80% coverage), but the description adds a critical constraint: 'up to 20 named UI slots' which is absent from the schema. It also explains the purpose of 'task' as resolving ambiguous slot names, adding meaning beyond the schema's example.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Pick a coherent Digche icon set for up to 20 named UI slots in one call', clearly stating the verb, resource, and scope. It explicitly contrasts with per-icon search ('Use this instead of one search per icon'), distinguishing it from the search_icons sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It says to use this tool when laying out a screen and instead of one search per icon, providing a clear alternative. It also instructs users to 'Give the overall task so ambiguous slot names resolve correctly', which guides effective use. It doesn't enumerate other sibling tools, but the primary alternative is named.

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

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TDQS

A3.9/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose: searching, retrieving, listing, previewing, recommending, and finding replacements. Even though search_icons and preview_icons both accept queries, their intents (discovery vs. comparison) are clearly differentiated in the descriptions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (find_replacement, get_icon_svg, list_categories, preview_icons, recommend_icons, search_icons), making the API predictable and easy to navigate.

Tool Count5/5

With 6 tools, the set is well-scoped for an icon library server. Each tool serves a essential step in the icon selection workflow without redundancy or bloat.

Completeness4/5

The tool surface covers the full lifecycle: discovering categories, searching, previewing, retrieving SVGs, recommending sets, and replacing third-party icons. The only minor gap is the absence of a direct metadata-only lookup, but search summaries and SVGs largely fill this need.

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