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

With no annotations, the description carries full responsibility. It discloses the data source (durable snapshot store), a data limitation (suppressed below 5 posts), and clarifies that it is derived rather than a direct API proxy. This is substantial behavioral context, though it omits auth requirements or rate limits.

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 relatively short (two sentences) and the first sentence front-loads the purpose. However, the second sentence is dense with jargon and includes marketing fluff like 'owning the curve', which does not add functional clarity. Some phrases could be simplified without loss of meaning.

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 description covers key computational aspects and mentions a suppression threshold, and an output schema exists so return values need not be described. Yet it is vague about the overall output structure, data freshness, and prerequisites beyond having a harvested corpus, leaving some gaps for a complex analytics 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?

The description provides no information about the two parameters (npub, dpop_token) and does not explain dpop_token's role. Schema coverage is only 50% (npub described, dpop_token not), so the description fails to compensate for the gap, leaving the token parameter ambiguous.

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 computes derived reach scores across a harvested post corpus, enumerating specific metrics (escape velocity, breakout ratio, link-placement cohort medians, snippet/voice attribution). The verb+resource are present, and the mention of 'not proxying a single X endpoint' distinguishes it from direct metric tools, though it could be more explicit about the overall 'post performance' scope.

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 usage for aggregated, derived analytics across multiple posts and contrasts with 'proxying a single X endpoint', giving a sense of when it's appropriate. However, it does not explicitly name alternative tools or state when to use this instead of excalibur_get_post_metrics or excalibur_harvest_metrics, and no exclusions are mentioned.

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