SRI — MCP Server Inspector

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

Annotations only declare readOnlyHint and openWorldHint. The description adds substantial behavioral context: it is free and keyless, reads published source, anchors each observation to file:line, reports 'not a safety verdict,' and explains that an empty result is not proof of safety. This goes well beyond the structured 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 dense but well-organized: a one-sentence value proposition, a bolded directive, bullet points of typical findings, clear exclusions, and a final corpus note. Every sentence adds distinct information, and the most important guidance is 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 security-relevant tool, the description covers scope, corpus size, input formats, limitations, exclusions, and the meaning of empty results. An output schema exists, so return structure is already provided. The agent has enough context to invoke it correctly and interpret results.

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 name, version, ecosystem, and l402_token thoroughly. The description reinforces the ecosystem restriction and gives usage context, but mostly echoes schema details. Baseline 3 is appropriate since the schema carries the semantic load.

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 states a precise verb and resource: 'Reads the published source of an MCP server and reports what it actually does — each observation anchored to a file:line with the code quoted verbatim.' It also explicitly distinguishes itself from analyzing npm/PyPI libraries记者 and from the sibling coverage tool, so an agent can tell exactly what this tool does.

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 an explicit imperative: 'Call this before connecting to, installing, or invoking an MCP server you have not read yourself.' It also gives exclusion criteria: 'Do NOT call this for ordinary npm or PyPI libraries,' and clarifies that it reports observations rather than a safety verdict.

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 include readOnlyHint: true, but the description adds significant transparency beyond that: 'No arguments', 'Returns how many... and the share of them with each category', and explicitly states limitations: 'aggregate counts only - no per-server findings, and no verdict about any individual server.' This fully clarifies behavioral scope.

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 extremely concise—two sentences. The first sentence states the function, and the second gives usage context and limitations. No filler or redundant phrases. It is front-loaded with the key information and 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 (no params, simple aggregate output), the description fully covers what it does, how to use it, and what it doesn't do. The existence of an output schema covers the return format, so the description doesn't need to detail that. It is complete and actionable.

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?

There are zero parameters, and the schema is empty with 100% coverage. The description even states 'No arguments', which aligns with the schema. Since there are no parameters to explain, a baseline of 4 is appropriate; the description doesn't need to add param semantics.

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 function: 'Returns how many MCP servers have been read at source level, and the share of them with each category of finding.' It also differentiates from the sibling tool by explicitly noting it provides only aggregate counts with 'no per-server findings', making its purpose distinct.

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 explicit guidance: 'Use this to judge whether checking a specific server is worth it before you look one up.' It also implicitly contrasts with the sibling tool by stating it does not give per-server details, which orients the agent on when to use this vs. check_mcp_server.

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