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

No annotations exist, so the description carries the disclosure burden, and it does add real behavioral context the empty schema cannot: a fixed 7-day window and the four metrics reported. It stops short of addressing data freshness, caching, or the read-only nature explicitly, which keeps it out of the top band.

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?

Two tight sentences with no repetition or filler; the capability statement comes first and the usage cue follows. Nothing could be removed without losing information.

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?

An output schema exists, so return-shape details are documented elsewhere; for a no-param summary tool the description only needs to say what is summarized and when to reach for it, which it does. Nothing an agent needs to call it correctly is missing.

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 there is no parameter semantics to explain and the baseline for a no-param tool applies. The description correctly avoids inventing filters or options that the empty schema does not support.

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?

States a specific verb ('Summarize') plus the exact resource ('the A2A agent registry') and enumerates the content of the snapshot (total, verified, new, left). The 'A2A agent registry' scope clearly separates it from siblings like get_llm_summary and get_mcp_ecosystem_summary, which cover different domains.

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?

Explicitly gives a trigger condition: 'Use when the user asks how the AI agent registry is growing.' That is clear usage context, but it names no exclusion or alternative tool for related questions (e.g. ecosystem-wide versus registry-only growth), so it stops short of a full when/when-not pairing.

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