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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real behavioral context beyond that: the counts are 'live', there is a rolling 24-hour traffic summary, and it explicitly enumerates what the scoreboard 'deliberately cannot measure' — a valuable limitation disclosure rarely seen.

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?

Front-loaded imperative in caps, then contents, then next steps — good ordering. The middle enumeration is long and could be trimmed, but each clause names a distinct measurable category rather than padding.

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?

With no output schema, the description carries the return-value burden and does so thoroughly: it lists the returned count categories, the traffic summary, and the explicit limitations list. An agent knows what it will get before calling.

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 takes zero parameters, so the 4 baseline applies; there is no argument semantics to explain. The description correctly spends no space on parameters.

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?

Specific verb ('Returns live counts') with an enumerated resource list: trial registrations, canonical trials, cross-registry trials, reframed articles, cure research items, objectives, open questions, abstraction nodes. This cleanly separates it from siblings like get_trial_stats, get_trial_coverage and data_freshness.

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?

Opens with an explicit trigger condition ('CALL THIS BEFORE QUOTING THE SIZE OF THIS INDEX') and closes with named alternatives for adjacent needs (get_api_status for reliability, get_open_questions for work). When-to-use and where-to-go-next are both stated.

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