Fetch the SVG markup for up to 20 Infyicon icons in one call (pass an array of ids). Use when building a UI or icon set so you grab several at once instead of calling get_icon_svg repeatedly.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes | Array of icon ids, e.g. ["home-2_101", "gear-1_202"] |
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 adds useful behavioral context such as the 'up to 20' limit and 'one call' semantics. However, it does not disclose what happens for invalid IDs or when more than 20 are passed, nor the exact response shape.
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 efficient sentences: the first states the action and constraint, the second provides the usage context and differentiates it from the sibling. There is no filler or 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 single-parameter tool with high schema coverage, the description is largely complete: it gives the action, batch size, and usage context. The only notable gap is the absence of an output-shape note, but given there is no output schema, the description still provides enough to invoke the tool 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 input schema already provides 100% coverage, including format and an example for the sole required parameter. The description adds the 'up to 20' cap, which is helpful, but it does not add significant meaning beyond what the schema already conveys.
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 specific verb ('Fetch'), names the resource ('SVG markup for up to 20 Infyicon icons'), and specifies the input shape ('pass an array of ids'). It clearly distinguishes itself from get_icon_svg by emphasizing the batch capability.
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 states when to use the tool ('when building a UI or icon set') and explicitly contrasts it with an alternative ('instead of calling get_icon_svg repeatedly'). It does not spell out exclusions, but the context is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clear, distinct roles: search, list categories, and fetch SVG/PNG by id. Some overlap exists because search_icons already returns SVG and PNG URLs, but get_icon_svg/get_icon_png are clearly meant for direct retrieval by known id.
The naming pattern is generally consistent using verb_noun style: get_icon_svg, get_icon_png, list_categories, search_icons. uicons_lookup deviates slightly by starting with a product name instead of a verb, but it is still understandable and similar in spirit.
Five tools is a well-scoped size for an icon service: search, browse categories, retrieve two format types, and check webfont usage. Each tool has a clear purpose and none feel redundant enough to remove.
The core icon workflow is covered: search, category discovery, SVG/PNG retrieval, and UI-font lookup. Minor gaps exist around category-specific icon listing or richer metadata, but agents can successfully search and fetch icons end-to-end.