Official ImageKit developer server: search the docs and build transformation URLs. No sign-in.
Scored across 2 tools
The two tools have clearly distinct purposes: one searches documentation, the other builds transformation URLs. No overlap or ambiguity exists between them.
Both names are readable and descriptive, but they follow different patterns: 'search_docs' is verb_noun, while 'transformation_builder' is noun_noun (with builder as agentive). The mixed phrasing is noticeable, though each is self-explanatory.
With only 2 tools, the server feels very thin for the ImageKit domain, which typically includes asset management, uploads, and transformations. The pair covers only a narrow slice of developer workflow, leaving most interactions unaddressed.
The tool surface is severely limited: it provides doc search and URL building, but no tools for uploading, listing, deleting, or transforming assets directly, nor any management endpoints. The purpose is unclear beyond these two utilities, leaving major workflow gaps.
Search ImageKit documentation using semantic search.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language search query about ImageKit features, APIs, SDKs, etc. | |
| sources | No | Optional list of documentation sources to search within. If not provided, sources are auto-detected from the query. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 mentions 'semantic search,' which hints at search behavior, but does not disclose side effects, permissions, rate limits, or any operational characteristics beyond the basic read action. The description is safe and accurate but thin on behavioral detail.
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, well-structured sentence that is front-loaded with the key action and object. There is no redundant information, and it earns its place without extra fluff.
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 search tool with full schema coverage and an output schema, the description is adequately complete. It covers the primary purpose and the parameters are self-explanatory. However, it lacks usage examples or mention of typical scenarios, which would elevate it further, but is not critical given the tool's simplicity.
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 provides 100% coverage of the two parameters ('query' and 'sources'), each with clear descriptions and defaults. The tool description adds no extra meaning or examples beyond the schema, so the baseline of 3 for high schema coverage 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 states a specific verb ('Search'), a clear resource ('ImageKit documentation'), and a distinguishing method ('semantic search'). It is immediately obvious what the tool does and it is distinct from the sibling tool 'transformation_builder', which is about building transformations rather than searching docs.
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 usage for searching documentation, but it provides no explicit guidance on when to use this tool versus the sibling tool 'transformation_builder'. There are no exclusions, alternatives, or prerequisites mentioned, leaving it to the agent to infer context from the tool name and purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Build an ImageKit image/video transformation URL from a natural language description.
| Name | Required | Description | Default |
|---|---|---|---|
| src | No | Optional source image URL. If not provided, a default sample image is used. | |
| query | Yes | Natural language description of the desired transformation (e.g. "resize to 800x600", "add blur and grayscale", "remove background"). | |
| fetch_url_to_check | No | Whether to verify the generated URL is accessible via CDN. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
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 only mentions building a URL, but does not disclose that the tool may perform network requests (e.g., via fetch_url_to_check), any authentication requirements, or side effects. This is a significant gap for an external-service 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?
The description is a single, focused sentence that states the tool's core purpose without any fluff. It is front-loaded with the key action and resource, making it easy for an agent to quickly grasp the tool's function.
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 description is minimal but the schema covers parameter details, and there is an output schema present. However, it does not mention the optional src parameter or the URL verification behavior, nor any limitations of the natural language processing. For a tool with no annotations, the description could provide more context to be fully self-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?
Schema description coverage is 100%, and the schema already provides detailed descriptions for all three parameters (src, query, fetch_url_to_check). The description does not add additional semantic context beyond what the schema gives, so the baseline score of 3 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 clearly states the tool's action (build), the resource (ImageKit image/video transformation URL), and the input (natural language description). This is a specific verb+resource description that differentiates it from the only sibling, search_docs, which is obviously unrelated.
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 usage context by specifying it builds transformation URLs from natural language, but it does not explicitly state when to prefer this tool over alternatives or mention any exclusions. With only one sibling (search_docs) that is clearly distinct, the usage is inferred rather than explicitly guided.
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.
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