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

Annotations declare readOnlyHint=true, but the description adds substantial behavioral context: it is derived from an hourly rollup, it is keyless-cacheable, and it explains the distinction between total_count (all IDs ever) and registered_count (LIVE IDs). This goes well beyond the annotation and informs the agent about data freshness and caching semantics. No contradiction with 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 compact (three sentences) and front-loads the core purpose. It uses a clear title and then provides necessary details without fluff. Every sentence adds value: the facets, the count semantics, and the caching note. Well structured.

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 must explain what is returned. It does so thoroughly: lists the facet dimensions, mentions registered share and provenance split, explains total_count vs registered_count, and notes the hourly rollup freshness. This is sufficient for an agent to understand the tool's output without needing an output schema.

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?

There are zero parameters, so the input schema is empty. The baseline for zero parameters is 4. The description doesn't need to elaborate on parameters; it focuses on output semantics, which is appropriate. Since there are no parameters, no additional information could be added.

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 identifies the tool as providing global participant facet counts across multiple dimensions (country, scheme, smp, ap, doctype, transport_profile), plus registered share and provenance split, with an estimated total. It distinguishes itself from sibling tools like get_participant (individual) and get_participant_stats_history (historical) by focusing on current rollup stats. The verb 'get' and resource 'participant stats' are specific and unambiguous.

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 notes it is keyless-cacheable and safe for the marketing site to hit directly, which gives a usage context. However, it does not explicitly state when to use this tool instead of get_participant_stats_history or other stats tools. The guidance is implied (current vs historical) but not spelled out as an alternative, so the agent must infer.

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