MetaMask Embedded Wallets (Web3Auth) MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds behavioral context by listing sources (Algolia, llms.txt, GitHub MDX) and specifying 'full content', but it does not disclose return format or potential errors. This is a moderate addition, consistent with 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 single, front-loaded sentence that clearly communicates the core function and includes useful source information without any fluff. It is appropriately concise and well-structured.

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 read-only tool with one parameter and no output schema, the description adequately covers the main purpose and inputs. It lacks details like return format or error handling, but these are minor for a straightforward fetch operation and are not essential given the simplicity and annotations.

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 schema already describes the 'url' parameter with an example, and the description merely repeats 'by URL'. With 100% schema coverage, the baseline is 3, and no additional parameter meaning is provided beyond what the schema already offers.

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 verb ('Fetch'), resource ('documentation page'), and method ('by URL'), making the tool's purpose obvious. However, it does not explicitly differentiate from sibling tools like search_docs or get_example, so it misses the full 5-point criteria.

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 explicit guidance is provided on when to use this tool versus alternatives. The description implies usage when a URL is available, but it does not mention search_docs or other siblings, nor any exclusions or prerequisites beyond having a URL.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, openWorld, and idempotent hints, so the description carries a lower burden. It adds useful context that the source code comes from GitHub and is 'complete', but does not disclose potential response size or external dependency behaviors 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, front-loaded sentence with no filler words. It immediately states the action and the object, meeting conciseness and structural requirements perfectly.

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 has no required parameters and no output schema, the description could clarify whether at least one filter is needed or if name alone suffices to fetch an example. However, the schema itself provides comprehensive parameter documentation, and the tool's purpose is straightforward.

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 100% description coverage for all parameters, each with clear examples and enum definitions. The description does not add additional meaning beyond the schema, so baseline 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 uses a specific verb ('Fetch') and resource ('complete source code of a Web3Auth integration example from GitHub'), clearly distinguishing it from sibling tools like get_doc, get_sdk_reference, and search tools.

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 clearly implies usage for retrieving example source code, and the sibling names provide context for alternatives. However, it does not explicitly state when to use this vs. other tools or mention any exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds context that the source comes from open-source repositories, implying public access and no authentication. It also lists example content facets (types, interfaces, hooks). No contradiction with 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?

A single concise sentence that front-loads the action ('Fetch SDK source code') and specifies the resource and domain. No filler or redundancy.

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 read-only retrieval tool with a detailed schema and three safety hints, the description adequately captures the tool's purpose. No output schema exists, so return format is not required. The description is complete for an agent to decide when to use it.

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%: all three parameters (platform, focus, module) have descriptions with enums and a default. The tool description itself does not add parameter-specific information, so it relies on the schema. With high schema coverage, a 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 uses 'Fetch SDK source code' with a specific resource and domain ('open-source Web3Auth repos'). It clearly distinguishes from sibling tools like get_doc and get_example by focusing on source code rather than documentation or examples.

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 use for retrieving SDK source code, contrasting with siblings for docs/examples. However, it does not explicitly name alternatives or provide exclusion criteria. The module parameter guidance ('Call without module first') offers internal usage help but not inter-tool guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe read operation. The description adds minimal context (the forum URL) but does not elaborate on pagination, result structure, or whether query and topic_id can be combined.

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, front-loaded sentence with no wasted words. It efficiently conveys the tool's purpose without redundant details.

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 simple read-only nature, good annotations, and complete schema, the description is sufficient. It lacks details on result formatting or parameter interaction, but these are not critical for a search/fetch tool with no required parameters.

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%, with detailed descriptions for both query and topic_id. The description's 'Search or fetch posts' reflects these parameters but adds no additional semantic meaning beyond what the schema already provides.

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 action ('Search or fetch posts') and the specific resource ('MetaMask Embedded Wallets community forum'), which distinguishes it from sibling tools like search_docs that target documentation.

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 makes it clear that this tool is for community forum posts, implying when to use it. However, it does not explicitly state exclusions or alternatives, such as 'for documentation use search_docs'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.