Search MetaMask Embedded Wallets documentation (Algolia) and example projects. Returns doc page links with snippets and matching examples.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Filter examples by blockchain family | |
| query | Yes | What you are looking for -- e.g. 'React custom auth', 'Android deep linking', 'JWT grouped connections' | |
| category | No | Filter examples by category | |
| platform | No | Filter examples by platform |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, and idempotent hints, so the safety profile is covered. The description adds useful behavioral context by naming the Algolia backend and specifying that results include links, snippets, and matching examples, which goes beyond the annotations.
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 compact two-sentence structure, front-loaded with the action and resource, and every sentence adds value. There is no redundant or extraneous content.
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 the tool's moderate complexity, rich parameter schema, and strong annotations, the description sufficiently conveys purpose and output. It does not mention result limits or pagination, but for a search tool with no output schema, stating that it returns links with snippets and matching examples is reasonably complete.
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 with descriptions for all four parameters, including detailed enums for chain, category, and platform. The description itself does not add further parameter-specific semantics, so the baseline score 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 uses a specific verb ('Search') and clearly identifies the resource ('MetaMask Embedded Wallets documentation (Algolia) and example projects'). It also states the return value ('doc page links with snippets and matching examples'), which distinguishes it from sibling retrieval tools like get_doc and get_example.
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 this tool is for searching across docs and example projects, giving clear context for when to use it. However, it does not explicitly mention alternatives or exclusions, leaving room for a stronger differentiation from siblings like search_community.
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.
Each tool targets a distinct resource: documentation pages, example code, SDK source, community posts, and docs search. The two search tools are clearly separated by source (docs vs community). No overlapping purposes.
All tool names follow a consistent verb_noun pattern: get_ for fetching specific resources, search_ for searching. Naming is uniform and predictable.
Five tools is well-scoped for a documentation-focused server. Each tool fills a distinct role without redundancy or unnecessary bloat.
The tool surface covers the full discovery and retrieval lifecycle for documentation, examples, SDK sources, and community content. No obvious missing operations for the stated purpose.
