mcpindex

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

No annotations are provided, so the description carries the full burden. It discloses that the assessment is advisory, conformance is monitored not enforced, and verdicts may be UNVERIFIED. However, it does not state whether the tool is read-only or has any side effects.

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 purpose, and contains no wasted words. Every sentence adds value.

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 simplicity (one parameter, no output schema), the description adequately covers purpose, usage guidance, and behavioral caveats. Missing a note about idempotency or safety, but overall 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?

Input schema covers 100% of the single parameter with a clear description. The tool 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 clearly states it performs an 'aggregated pre-flight trust assessment across all tools on an MCP server' and explicitly distinguishes from sibling check_tool_trust by noting 'same verdict shape as check_tool_trust'.

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 explicit usage context: 'Use for "is THIS server worth integrating?" decisions.' It also includes advisory notes about conformance monitoring and unverified verdicts, but does not explicitly list when not to use or alternatives.

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 that v1 only returns REVIEW or UNVERIFIED, that ALLOW/DENY are reserved, and that it is not the in-path gate. It does not mention side effects or authentication needs, but given it is an advisory-only tool, the provided transparency is sufficient.

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 concise: three sentences, each adding value. It is front-loaded with the tool's purpose and efficiently covers return value, limitations, and usage guidance without 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?

Given the tool has two required parameters, no output schema, and no annotations, the description adequately covers purpose, return value, limitations, and interpretation guidance. It could mention that the tool is safe to call (no side effects), but overall it is sufficient for the complexity.

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 the schema already documents both parameters clearly. The description does not add any additional information about the parameters beyond what is in the schema, so it meets the baseline of 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?

Description clearly states the tool is a pre-invocation advisory screen for a specific tool on an MCP server, returning an advisory verdict with specific directives. It distinguishes itself from the in-path gate and provides clear context, differentiating it from sibling tools like assess_server or search_mcp_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?

The description provides context for when to use it (pre-invocation) and how to interpret results (UNVERIFIED requires human review). However, it does not explicitly mention when not to use it or provide alternatives among siblings, so it lacks explicit 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?

No annotations provided, so description carries burden. It mentions output fields (quality scores, install paths, env vars), giving some transparency. However, it does not disclose whether the tool modifies state or requires specific permissions, leaving gaps for a read-only operation.

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?

Single sentence with no wasted words, clearly communicates core purpose. Could add more structure (e.g., bullet points for output fields), but remains 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 one simple parameter and no output schema, description explains what the tool does and outputs. Lacks details on return format or how to interpret results, but is minimally sufficient for a straightforward comparison 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 describes 'slugs' as 'Server slugs to compare' with min/max constraints. Description reiterates '2-5 MCP servers' but adds no new meaning about parameter format or examples. Since schema coverage is 100%, 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?

Description clearly states it performs side-by-side comparison of 2-5 MCP servers, listing specific aspects (quality scores, install paths, env vars). This distinguishes it from sibling tools like assess_server (single server) and search_mcp_servers (search).

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 on when to use this tool vs alternatives. Implies usage for comparing multiple servers, but does not mention when not to use or which sibling tool to choose instead.

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 are provided, so the description carries the full burden. It discloses the return format but does not explicitly state that the operation is read-only, has no side effects, or any authentication requirements.

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 concise sentences: one for purpose and one for return format. No wasted words, front-loaded with key information.

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 2-parameter tool with no output schema, the description is largely complete. It could elaborate on the JSON structure, but 'ready to paste' sufficiently conveys the value.

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 the description adds value by clarifying that server_slug comes from search or recommend results, which is not in the schema beyond 'Slug of the server'.

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 'get' and the resource 'install command' for a given MCP server and client, and it distinguishes from sibling tools by focusing on generating a paste-ready JSON block.

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 needing an install command) but lacks explicit guidance on when not to use or alternatives, such as assess_server or search_mcp_servers.

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 explains the tool returns top 3 picks with reasoning, install commands, and scores. It does not mention any destructive actions or auth needs, which is acceptable for a read-only recommendation.

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 concise sentences; the first states purpose and output, the second gives usage guidance. No wasted words, front-loaded.

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 one-parameter tool with no output schema, the description explains the return format (top 3, reasoning, install commands, scores). It is nearly complete but could mention the source of recommendations (e.g., a database or live 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 100%, and the description adds an example ('read PDFs and write to S3') beyond the schema's description, providing clearer guidance for the single 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 title and description clearly state the tool recommends MCP servers for a task. The description specifies it returns top 3 ranked picks with reasoning, install commands, and quality scores, distinguishing it from siblings like 'search_mcp_servers' and 'assess_server'.

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 explicitly says 'Use this when the user asks for the right MCP server for a task they want to do.' It does not specify when not to use, but the sibling list implies alternatives.

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 are provided, so the description must carry the full burden. It mentions the search method (keyword + semantic) but does not disclose whether it's read-only, has rate limits, or requires authentication. For a simple search tool, the behavioral implications are largely implied, but more explicit detail would improve transparency.

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 consists of two concise sentences with the key action front-loaded. No redundant information, every word contributes to clarity.

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 3 parameters (all documented in schema) and no output schema, the description explains the search scope and use case adequately. However, it does not mention the format of results or that the operation is safe (read-only), which would be helpful for a complete picture.

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%, meaning the schema already describes all three parameters. The tool description adds no additional meaning beyond what is in the schema, so the 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 clearly states it performs keyword and semantic search across indexed MCP servers, differentiating it from siblings like assess_server or recommend_mcp_for_task which have different purposes.

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 explicitly says to use when the user knows the tool category but not the server, providing a clear usage context. It does not list when not to use or name alternatives, but the context is sufficiently directive.

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