Solana MCP by Vybe

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

The annotations already declare readOnlyHint=false, destructiveHint=true, and openWorldHint=true, so the safety profile is covered, but the description adds no further behavioral context such as response shape, external side effects, auth implications, or error behavior. It neither contradicts the annotations nor enriches them.

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, which is appropriately concise. It is slightly close to the title but does add the 'given HAR request object' qualifier, so it earns its place.

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 tool that can execute arbitrary API requests with destructive and open-world annotations and no output schema, one sentence is insufficient. The agent is not told what the response will look like, whether the request is sent as-is, or how this tool fits with the sibling discovery tools, leaving important execution context undocumented.

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 is highly detailed, covering the HAR request shape, method options, headers, query strings, and postData alternatives with descriptions on all fields. Since schema description coverage is 100%, the description does not need to add parameter semantics, and the baseline 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 concrete action, 'Executes an API request,' and identifies the input as a HAR request object, which clearly separates it from the read-only siblings get-endpoint, list-endpoints, and search-endpoints. It does not explicitly contrast itself with those siblings, so it misses the top mark.

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 gives no guidance on when to use this tool versus the sibling discovery tools, nor any prerequisites such as finding an endpoint first or cautioning about destructive side effects. The presence of sibling tool names alone does not explain the selection logic.

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?

The description does not contradict the annotations, which already declare this a read-only, non-destructive operation. It adds useful context about what the response includes (security schemes and servers), but it does not disclose details like authorization requirements, error behavior, or whether the endpoint details are always available.

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 front-loads the action and resource, then adds the most relevant detail about the return value. Every word contributes.

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 two-parameter, read-only tool with well-documented schema and annotations, the description covers the essential purpose and return contents. The only gap is the lack of an output schema and a more explicit return contract, but the tool's low complexity makes this acceptable.

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 already describes both parameters (path and method) with clear examples, so the description adds no additional parameter-level meaning. This matches the baseline of 3 given 100% schema description coverage.

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 ('Gets detailed information') and its specific resource ('a specific API endpoint'), and even previews the key response content ('security schemes and servers'). This is distinct from list-endpoints and search-endpoints, which deal with collections rather than a single endpoint.

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 phrase 'specific API endpoint' implies the tool is meant for retrieving details about one endpoint identified by path and method, but it does not explicitly say when to use it over search-endpoints or list-endpoints. No exclusions or alternative routing are mentioned.

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 destructiveHint=false, so the safety profile is covered. The description adds value beyond that by specifying the output organization ('organized by path') and the compatibility with get-endpoint's input, which is useful behavioral context for an 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?

Two sentences with no redundancy. The primary function is front-loaded, and the follow-up workflow is stated efficiently without wasting words.

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, zero-parameter listing tool with annotations covering safety, the description fully explains what is returned, how it is organized, and how to proceed. Nothing essential for calling the tool correctly 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 takes zero parameters, so the schema is trivially covered at 100%. Per the rubric, 0 params yields a baseline of 4; the description correctly omits parameter details because none exist.

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 lists all API paths, HTTP methods, and summaries, organized by path. This distinctively differentiates it from siblings like get-endpoint (specific endpoint) and search-endpoints (filtered lookup), leaving no ambiguity about the resource and verb.

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 provides clear context for using this tool as an overview before drilling into a specific endpoint, and explicitly notes that results can be passed to get-endpoint. It does not explicitly exclude alternatives like search-endpoints, but the 'all paths' phrasing implies exhaustive listing as the primary use case.

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?

Annotation contradiction: readOnlyHint=true claims the tool does not modify state, while the description says 'pay-per-call USDC on Solana,' which implies a financial side effect. The description also does not explain how the payment works, what is charged, or what side effects occur.

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 sentence with the condition front-loaded and the purpose stated compactly. The parenthetical examples add useful context without unnecessary 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?

There is no output schema and no description of what the tool returns, so an agent cannot know how to use the result or chain it with the subsequent endpoint call. The phrase 'the same endpoint' is ambiguous because the tool takes no parameters to identify which endpoint is being referenced.

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 and 100% schema coverage, so there is nothing for the description to add at the parameter level. The baseline of 4 applies because the schema already fully describes the parameters.

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 specifies the resource and scenario: accessing a Vybe endpoint without an API key via x402 pay-per-call USDC on Solana. The verb 'access' is more generic than 'pay' or 'authorize', and it does not explicitly differentiate from sibling tools, but the name and context make the purpose reasonably clear.

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?

It gives an explicit trigger condition: use this before calling any Vybe endpoint without an API key, with helpful examples like AI agent, throwaway script, and premium-only path. It does not explicitly name the alternative path or exclusion cases, but the intended usage is clear enough.

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 destructiveHint=false, covering safety. The description adds useful behavioral context by stating that search results can be passed directly into 'get-endpoint', implying the output is compatible with that tool's input. It also mentions 'deep search' but doesn't detail pagination or rate limits; given annotation coverage, the added workflow info justifies a 4.

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 sentences, front-loaded with the core purpose, and every clause contributes value. No filler or repetition.

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 single-parameter search tool with annotations covering safety and no output schema, the description is quite complete. It states what it does, when to use it, and how results feed into 'get-endpoint'. It doesn't describe the return format in detail, but the workflow hint mitigates that. Missing explicit mention of alternatives or edge cases, but adequate for typical agent use.

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%, so the parameter 'pattern' is documented. The description adds meaning by explaining that the pattern searches through 'paths, operations, and parameters', which goes beyond the schema's generic 'Search pattern (case-insensitive)'. This clarifies what the pattern can match, adding value.

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 purpose: performing a deep search through paths, operations, and parameters to discover relevant API endpoints. It uses a specific verb ('search') and resource ('API endpoints'), and clarifies the scope of the search. However, it does not explicitly differentiate from sibling 'list-endpoints' (which likely lists all endpoints), leaving some ambiguity about when to choose this over listing.

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 provides clear usage context: 'Use this tool to find specific API capabilities, required parameters, or data models based on search keywords.' It also notes that results can be passed to 'get-endpoint', implying a workflow. However, it does not explicitly state when not to use it or mention alternatives like 'list-endpoints' or 'execute-request', so exclusions are absent.

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