Find relevant information across accessible markdown knowledge spaces, returning cited sources for AI assistants.
Search accessible markdown knowledge spaces and return citations.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| space | No | ||
| include_groups | No | ||
| include_personal | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the base safety is known. The description adds context about accessibility scope, content type (markdown), and output form (citations), but does not describe defaults, scope toggles, or result handling 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?
One compact, front-loaded sentence that states action, scope, and return value without redundant filler.
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 5 undocumented parameters and only a readOnlyHint annotation, the description is too thin. The output schema helps with return values, but the agent still lacks parameter semantics and usage context to tailor a search.
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% across 5 parameters, so the description must compensate, but it mentions none of query, limit, space, include_groups, or include_personal. The agent cannot learn parameter meanings from the description.
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 and resource: searching accessible markdown knowledge spaces. It also differentiates from sibling tools like gateway_knowledge_document_search and gateway_memory_search by highlighting 'markdown knowledge spaces' and the return of 'citations'.
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?
No guidance is given on when to use this tool versus alternatives such as gateway_knowledge_document_search, gateway_memory_search, or gateway_company_search. The description implies a context but provides no exclusions or selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.