MCP Registry Validator — Check Endpoints Actually Resolve

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

With no annotations present, the description carries the full burden of behavioral disclosure. It reveals that the tool performs a live probe, checks multiple runtime aspects, remembers prior checks ('since the last check'), and is intended as a pre-dependency validation. This adds meaningful non-obvious context beyond what the schema shows, though it does not mention potential network latency or failure behavior.

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 provides necessary information. There is no fluff 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?

The tool has no output schema, so the description must communicate what the caller gets. It does so by enumerating the probe results (alive, transport, tool count, schema change). It does not detail exact response fields or error cases, but for a moderate-complexity health probe this 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?

Schema description coverage is 100%, so the parameters are already well-documented in the schema. The description adds general context about probing and schema-change detection but does not add parameter-specific meaning beyond what the schema already provides. 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 specifies a concrete action ('Probe an MCP endpoint right now') and enumerates the exact outputs: liveness, transport, tool count, and schema-change detection. It distinguishes itself from siblings like check_schema_drift by positioning itself as a broader initial readiness probe rather than a focused drift check.

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 use case: 'Use before depending on a third-party MCP server.' This is clear contextual guidance, though it does not name sibling tools or state when not to use it, so it falls slightly short of a full 5.

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 provided, the description carries the full burden. It discloses a notable behavioral trait—'Schema drift fails quietly mid-run'—and explains that the tool diffing reveals changes. However, it does not mention network prerequisites, potential latency, or return format, leaving some behavioral aspects uncovered, though enough is provided for a basic 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?

The description is two sentences long, front-loaded with the core action ('Probe... diff...') and followed by a concise rationale. There is no redundant or filler text; every sentence adds value, earning a perfect score.

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 tool with one parameter and no output schema, the description covers the core functionality and even provides a motivating context ('why it is worth checking'). It does not explicitly describe the return structure or edge-case behavior, but given the low complexity, the description is largely adequate for an agent to select and invoke the tool correctly.

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 has 100% coverage for the single parameter 'url' with a clear description ('Public http(s) URL of the MCP endpoint to inspect'). The tool description adds no additional detail about the parameter, so the schema is the primary source of semantics; the baseline of 3 is appropriate for full schema 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 uses a specific verb ('Probe' and 'diff') and resource ('MCP endpoint tool schema against last stored snapshot'), clearly distinguishing it from generic checks. It enumerates the specific kinds of changes detected (tools added, removed, or description/inputSchema changed), making the purpose unambiguous and easily differentiated from sibling tools like check_mcp_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 description provides clear context on when this tool is useful: for detecting schema drift that 'fails quietly mid-run', implying it should be used proactively when schema changes need to be caught. It does not explicitly name alternatives or exclusion cases, but the rationale for using the tool is well communicated.

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?

There are no annotations, so the description carries the behavioral disclosure burden. It discloses key traits: reads stored history, does not probe (no network request), and returns 'last observed' data, indicating potential staleness. However, it does not mention error conditions, behavior when no history exists, or response format details.

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 short sentences, front-loaded with the core return value, and includes a concise behavioral disclaimer ('does not probe'). Every word earns its place; no fluff 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 tool with one parameter and no output schema, the description covers the essential return values (tool list and timestamp) and the key behavioral distinction (not probing). It does not specify the exact structure of the tool list (e.g., array of strings, objects), but that is a minor gap given the tool's simplicity.

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 has 100% coverage with a description for the only parameter ('url'), so the baseline is 3. The tool description adds no new semantic meaning about the parameter beyond what the schema provides; it only restates that the endpoint is an MCP endpoint.

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 that the tool returns the tool list last observed at an MCP endpoint, along with the timestamp of the most recent schema change. It uses a specific verb ('Reads stored history') and explicitly distinguishes from probing tools by saying 'does not probe', which also differentiates it from sibling tools like check_mcp_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 description provides clear context that this tool reads stored history and does not probe the endpoint, which implies it is for historical/cached data rather than live checks. However, it does not explicitly name alternative tools or state 'use this when...'—the guidance is implicit rather than explicit.

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 behavioral burden. It discloses that the tool reads stored history rather than probing, which prevents misuse for live checks. It also notes the 30-day maximum, adding useful operational context beyond the schema.

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 fluff, purpose first, then behavioral note. Every word earns its place and the structure is ideal.

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 tool with two parameters and no output schema, the description gives enough context to understand inputs and high-level output ('incident windows'). Some detail on return format is missing, but the tool's simplicity 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?

Schema coverage is 100%, so the baseline is 3. The description restates the window limit but adds no new parameter detail beyond what the schema already provides for 'url' and 'days.'

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 returns 'uptime history for an MCP endpoint' over a configurable window, including 'incident windows.' This specifies both the resource and scope, and stands apart from siblings like check_mcp_endpoint (likely live checks) and check_schema_drift.

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 explains this is read-only historical data by saying 'Reads stored history; does not probe,' implicitly distinguishing it from live-probing tools. However, it does not explicitly name an alternative tool for live checks, so it's not a full 5.

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