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

Annotations already declare read-only, idempotent, non-destructive behavior. The description goes further by disclosing keyless reads, the authoritative signals-sent count source, the CONFIGURED vs MEASURED SLO distinction, observation-window coverage, and explicit scope exclusions such as protocol conformance and operational health. This is rich behavioral context beyond the 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 longer than average but front-loads a one-line summary and uses bullets and delimiters to keep distinct concepts organized. Nearly every sentence adds decision-relevant detail; minor redundancy such as 'free' and 'keyless reads' appears twice, but the structure remains effective.

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 zero-parameter, read-only status tool with an output schema, the description fully covers what to expect: health fields, counters, SLO semantics, coverage window, and scope limitations. An agent has enough context to decide when to call this tool and interpret its result 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 tool has zero parameters, so the schema provides no parameter semantics and the description does not need to compensate. The 100% schema coverage is vacuous but harmless. A baseline of 4 is appropriate since parameter documentation is not applicable.

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 opens with a specific resource ('Instrument health, SLO standing, and the sample size behind every reading') and then enumerates concrete blocks: component health, system counters, and SLO. It names the authoritative source and relates it to the funnel and landing page, making the tool's role easy to distinguish from siblings.

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 trigger: 'Call this when any reading looks stale or absent, and to see exactly how small the sample behind a claim is.' It also warns that small samples cannot prove an edge. However, it does not explicitly name when not to use this tool or compare it against sibling tools by name, so it falls just short of a 5.

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