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

The description discloses key behavioral traits: default is read-only local observation, refresh=true triggers a real network refresh, and it covers specific reliability dimensions. The annotations already indicate openWorldHint=true and destructiveHint=false, and the description adds context about what 'refresh' does and what metrics are computed. It doesn't contradict annotations. It could add more about side effects of refresh (e.g., rate limits, cost), but the core behavior is transparent.

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, dense sentence that front-loads the core purpose (quantifying data source stability) and then lists the specific metrics. The second sentence clearly explains the two modes. Every part earns its place, and the structure is efficient for an agent 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 the tool's complexity (multiple statuses, rates, latency percentiles, schema drift signals) and the absence of an output schema, the description provides a solid overview of what the tool returns. It also clarifies the refresh behavior. It could be more complete by describing the output format or how to interpret the metrics, but for a monitoring tool with clear parameters, it's largely sufficient.

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 (refresh and platforms). The description adds context by explaining the default behavior (read-only local) and that refresh=true triggers a real refresh, which aligns with the refresh parameter. It also mentions '指定平台' (specified platforms) which maps to the platforms parameter. However, it doesn't add much beyond the schema's descriptions, 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 the tool's purpose: quantifying data source stability with specific metrics (UP/DEGRADED/DOWN/AUTH_REQUIRED/RATE_LIMITED, ok/usable rates, latency percentiles, consecutive failures, schema drift signals, history depth). It also distinguishes the default read-only local observation mode from the refresh=true mode. This is a specific verb+resource combination that differentiates it from sibling tools like trend analysis or content generation tools.

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 states when to use the default mode (read-only local observation) and when to use refresh=true (to perform a real refresh of specified platforms). It also mentions the platforms parameter for specifying which platforms to check. However, it doesn't explicitly name alternatives or exclusions among siblings, though the tool's unique focus on source reliability makes the usage context clear.

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