Search thousands of free SVG cut files & clipart. Free for commercial use, no attribution.
Scored across 4 tools
Each tool addresses a clearly distinct concern: fetching a specific design, retrieving license terms, listing categories, and searching designs. There is no meaningful overlap between get_design and search_designs because one is targeted lookup by slug and the other is keyword discovery.
All tool names follow a consistent lowercase snake_case verb_noun pattern: get_design, get_licence, list_categories, search_designs. The different verbs reflect different actions while remaining predictable and readable.
Four tools is a well-scoped size for a clipart catalog server focused on discovery, retrieval, licensing, and browsing. Each tool earns its place and the total feels neither thin nor bloated.
The core user journey—searching, viewing design details, checking license terms, and exploring categories—is well covered. A minor gap is the lack of an explicit tool to list all designs within a category, though search and category page URLs partially compensate.
Full details for one design by its page slug (e.g. "royal-crown-121000019").
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The design slug from a page URL or search result |
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 states what the tool returns ('full details') but does not explicitly declare it as read-only, mention error behavior for invalid slugs, or describe any side effects. The verb 'get' implies safety, but the description lacks explicit behavioral disclosure beyond 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 a single, focused sentence with no filler. It front-loads the purpose and includes an example, making it easy to parse. Every word contributes to comprehension.
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 one-parameter tool with no output schema, the description is sufficient: it specifies the input and implies the output (full details). It could optionally mention that it returns a single design object, but 'full details' covers that. Overall, there are no missing pieces that would prevent correct invocation.
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 100%, and the description adds a concrete example ('royal-crown-121000019') that clarifies the expected format beyond the schema's generic description. This extra context helps the agent construct a valid parameter, exceeding the baseline.
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 a specific resource ('design'), a specific identifier type ('page slug'), and provides a concrete example. It distinguishes this tool from siblings like search_designs (which likely returns a list) by specifying 'full details for one design.' No ambiguity.
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 implies the tool is used when you have a specific slug and need complete details, but it does not explicitly mention when to use it versus search_designs (e.g., to obtain the slug) or list_categories. No exclusions or alternative conditions are given, only implicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The licence terms for every design on InfySVG, in one paragraph.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It discloses the output shape ('in one paragraph') and implies a read-only operation by naming 'licence terms'. However, it does not explicitly address safety, side effects, or response format beyond the paragraph hint, leaving some assumptions to the agent.
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 extremely concise and every word contributes, with no filler. It is not phrased as an imperative sentence, but it is front-loaded with the key subject and scope.
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 zero-parameter, no-output-schema tool, the description covers the essential information: what is returned, for which designs, and in what format. It is slightly terse, but the low complexity of the tool means no significant context is missing.
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 and the schema has 100% coverage, so there are no parameter semantics for the description to clarify. This is the baseline score for parameterless tools.
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 resource (licence terms) and scope (every design on InfySVG), and the 'one paragraph' detail gives an output expectation. It lacks an explicit verb, but the tool name 'get_licence' and context make the action evident. It is distinguishable from siblings like get_design by its 'every design' scope.
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 does not state when to use this tool versus alternatives such as get_design or search_designs. It implies use when licence terms for all designs are needed, but no explicit when/when-not guidance or sibling differentiation is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Every category and seasonal collection with design counts and page URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 does disclose output scope ('Every category') and content ('design counts and page URLs'), which is useful for a simple read-only listing. It does not mention caching, authentication, or response format, but these are less critical for a no-parameter list 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?
A single sentence conveys the full return contents with no filler or redundancy. The most important information—what the tool returns—is stated directly.
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 0-parameter tool with no output schema, the description sufficiently explains what an agent will receive: categories, seasonal collections, design counts, and page URLs. It could add an explicit statement of the tool's read-only nature or result ordering, but the absence of parameters makes invocation unambiguous.
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 zero parameters, so the description has no parameter semantics to add. Per the baseline rule for 0-parameter tools, a score of 4 is appropriate.
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 the resource ('category and seasonal collection') and specifies the returned contents ('design counts and page URLs'). Although it lacks an explicit verb, the tool name 'list_categories' supplies the action, and the content clearly distinguishes it from design- or licence-focused siblings.
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 what the tool returns but gives no guidance on when to use it versus alternatives like search_designs or get_design. There are no exclusions, prerequisites, or context clues about the intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the InfySVG catalog of free SVG cut files by keyword. Returns matching designs with their page URLs. Send the user to the page for downloads — every page offers free SVG, PNG, DXF and PDF plus recolouring, no account needed.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results, default 10, max 30 | |
| query | Yes | What to search for, e.g. "crown", "halloween skull" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses that the tool returns page URLs rather than direct files, and adds that downloads need no account and include multiple formats plus recolouring. Ordering, pagination, and error behavior are not covered, but the most decision-relevant behavior is present.
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 focused sentences with the core action front-loaded. Every clause earns its place, including the downstream instruction to send users to the page for downloads.
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 search tool with two parameters and no output schema, the description provides purpose, return shape, and a clear follow-up action. It omits details like result ordering or empty-result behavior, but those are not necessary for correct invocation.
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 100%, with both query and limit already well described in the input schema. The description adds no additional parameter-level meaning, so the baseline score of 3 applies.
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 and resource ('Search the InfySVG catalog') and states the outcome (matching designs with page URLs). It does not explicitly contrast itself with sibling tools like get_design or list_categories, but the search intent is clearly distinct.
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 implies the tool is for keyword-based catalog searches and tells the agent to send the user to result pages for downloads. However, it does not state when to prefer this over get_design or list_categories, nor does it provide explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_designget_licencelist_categoriessearch_designsSearch thousands of free transparent PNG clipart images. Free for commercial use, no attribution.
Search 161,000+ free icons; get SVG (single/bulk), PNG, related icons, webfont classes. No API key.
320K+ open-source SVG icons: 12 tools, anonymous metadata search; SVG, exports, collections via Pro.
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