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

No annotations are provided, so the description carries full burden. It only states what the tool returns (grade and evidence) but does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or any side effects. This is insufficient for a tool with no annotation coverage.

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 action. Every word is necessary, no fluff. Ideal length for a simple 1-parameter tool.

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 no output schema, the description partially explains the return (full grade and verbatim probe evidence), but lacks context about when to prefer this tool over siblings like search_servers or list_grades. It also does not mention any output structure or size limits. Adequate but not thorough.

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% and schema already describes the parameter as 'Registry server name'. The description adds value by clarifying the exact format ('official registry name, e.g. com.healthai/radar'), providing a concrete example that aids understanding.

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 ('get') and resource ('full grade and verbatim probe evidence for one MCP server'), and specifies the input format ('official registry name, e.g. com.healthai/radar'). It distinguishes from siblings: list_grades likely returns multiple grades, search_servers searches servers, etc.

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 when to use (when you have the exact registry name and need grade/evidence for one server), but does not explicitly state when not to use or mention alternative tools. No exclusions or comparisons are provided.

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?

Without annotations, the description carries full burden. It adds behavioral context by stating 'Missing observations are explicitly unaudited, never treated as a pass,' which is a key trait beyond a simple read operation. However, it does not disclose whether the tool is destructive or has auth requirements, but since it's a read tool, this is minor.

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, no filler. First sentence states purpose and content; second adds crucial behavioral nuance. Every word 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 with one parameter and no output schema, the description covers what the receipt contains and a key behavioral trait. It could mention return format or data structure, but the agent can reasonably infer. Lacking output schema is compensated by detailed description.

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% for the single parameter 'name', described as 'Official registry server name'. The description does not add extra semantics 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?

Description explicitly states 'Get one MCP server's complete evidence receipt' and lists its components (operational grade, observations, field reports), which clearly defines the tool's purpose. It distinguishes itself from siblings like get_server_grade (which likely returns a simpler grade) and search_trust_evidence (which is a search tool for evidence).

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 comprehensive trust assessment but does not explicitly state when to use it versus alternatives like get_server_grade or search_trust_evidence. No when-not-to-use or prerequisite info is provided, relying on the user to infer based on the title.

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?

With no annotations, the description carries full transparency burden. It discloses the deterministic nature of grades with evidence and lists the exact fields returned. However, it does not mention ordering details or that the operation is read-only, though that is inferable.

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 wasted words. The first sentence immediately describes the core action, and the second adds return info. Highly efficient.

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 adequate for a simple list tool: it covers purpose, return fields, and source. It lacks explicit mention of ordering by grade or score, and does not clarify whether pagination is supported beyond the limit parameter. Slightly incomplete for full autonomy.

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% for the single parameter 'limit'. The description adds no extra meaning beyond the schema's own description. Baseline 3 is appropriate as schema already fully documents the parameter.

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 top graded MCP servers from a specific registry, and enumerates the fields returned per server (grade, score, latency, tool count, auth state). This is specific and distinguishes it from siblings like search_servers or get_server_grade.

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 viewing top servers but provides no explicit guidance on when to use this tool versus alternatives (e.g., search_servers, get_server_grade). No when-not-to-use or scenarios 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?

No annotations provided, so description carries full burden. It discloses tokenization, synonym expansion, ranking based on metadata and tool descriptions, and filters. However, it does not mention whether the search is read-only, rate limits, or authentication requirements. Still, it provides significant behavioral context.

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. The first sentence states purpose with an example, the second combines behavioral details and usage guidelines. No wasted words, front-loaded, and efficient.

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?

With 6 parameters, no output schema, and no annotations, the description covers query semantics, internal processing, filter support, and sibling differentiation. It lacks details on return format (e.g., what fields are returned) and pagination (limit parameter is mentioned but not behavior beyond max). Still, it is fairly comprehensive for a search tool.

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%, so baseline is 3. The description adds meaning by explaining that the query parameter accepts natural multi-word tasks and that tokenization/synonym expansion occurs. For other parameters (auth, category, minimum_grade, max_latency_ms), the description only references them generically, but the schema already describes them. Overall, the description adds moderate value beyond the schema.

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 searches the MCP evidence registry for servers using natural multi-word tasks, with an example. It distinguishes from sibling tools like search_tools (for tools) and get_trust_receipt/search_trust_evidence (for security evidence).

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?

Explicitly tells when not to use the tool and provides alternatives: 'Use get_trust_receipt or search_trust_evidence for security, data, citation, claim, and response evidence.' This gives clear guidance on when to use each sibling.

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?

With no annotations, the description discloses that the tool searches live tool names and descriptions, and returns matching tools with server, grade, and endpoint. This adequately describes read-only search behavior and output, though rate limits and auth requirements are not mentioned.

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?

Description is concise with a clear front-loaded purpose. Each sentence contributes value (examples, result details). Slightly verbose but 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 6-parameter search tool without output schema, the description covers purpose, usage context, and return format. Missing details like pagination or error handling, but adequate for basic understanding.

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 baseline is 3. The description adds limited meaning beyond the schema, such as framing the query parameter for 'capability or data type'. No additional context for optional 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 clearly specifies the verb 'search' and the resource 'actual tools that graded MCP servers expose', distinguishing it from server metadata searches. Examples like 'get weather' and references to sibling tools (e.g., search_servers) reinforce differentiation.

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?

Provides explicit when-to-use guidance ('Use this when you need a specific capability or data type') and concrete examples. Does not explicitly state when not to use, but the contrast with server-level search is implied.

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?

No annotations provided, so description carries the burden. It discloses that returns are verbatim observations with dates and source type, and explicitly states it does not produce a synthetic trust score. Lacks details on permissions or rate limits.

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, front-loaded with purpose and followed by usage examples and output details. No redundant or unnecessary 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?

Adequate overview but lacks detail on parameter semantics and output structure (no output schema). Given moderate complexity, more guidance on enum parameters would improve completeness.

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 50%, but the description adds no additional meaning to parameters like status or dimension beyond what the schema provides. It does not explain enum values or usage.

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 searches published trust evidence and field reports, with specific verb and resource. It includes example questions that distinguish it from siblings like list_grades or search_servers.

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?

Provides context with 'Use for questions such as...' but does not explicitly state when not to use or mention alternatives. Still, the context is clear enough for typical use.

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?

With no annotations, the description carries the full burden. It discloses two behaviors: reports are quarantined for human review and never auto-published. However, it lacks details on success/failure responses, rate limits, or error handling, leaving gaps in behavioral understanding.

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, no waste. Front-loaded with the verb and resource, followed by content scope and behavioral note. Efficient and easy to parse.

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 no output schema or annotations, the description covers purpose, content, and a key behavioral trait (quarantine). It may lack return value info, but for a submission tool this is acceptable. Most aspects are addressed.

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%, so all parameters (report, agent_name, server_name) have schema descriptions. The description adds minimal extra meaning beyond mentioning content guidelines ('what worked, what failed'). For high coverage, baseline is 3.

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: submit a field report about an MCP server that was actually used, detailing what worked, failed, or surprised. It distinguishes from siblings (e.g., list_grades, search_servers) which are read/search operations, making this the only write tool.

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 the tool should be used after using a server, and mentions reports are quarantined and not auto-published. It does not explicitly state when not to use it, but the context of siblings (all read/search) makes the use case clear.

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