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

No annotations were provided, so the description carries the full burden. It reveals that the tool is FREE, refreshes once per ingest day, and is LIVE while the USD panel is frozen, which is useful behavioral context. It does not explicitly state that it returns no card names or prices, but that is implied by 'as numbers — no card names or prices.' Given the lack of annotations, this is strong disclosure, though it could be more explicit about being a read-only, non-mutating operation.

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 a single dense paragraph, which is efficient but could be structured with a brief lead sentence and bullet points for the metrics. It front-loads the key point (market summary as numbers) and then details specifics. It's not overly verbose, but the wall-of-text format hurts readability.

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 tool with no output schema, the description thoroughly covers what the tool does, the data it provides, and usage guidance. It also differentiates from siblings. There is nothing missing that an agent needs to call it correctly or interpret results.

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?

With zero parameters, the schema is trivial (empty object), so the description carries the full burden. The description richly explains what the tool returns, covering counts, price bands, depth, movement, and Merkle root, which goes beyond what an empty schema could convey. Baseline for 0 params is 4, and the description meets that by clarifying the exact data content.

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 reports on the Japanese card market with specific metrics (counts, dealer bid/ask, depth, movement, Merkle root), and distinguishes it from related tools like market_snapshot by noting it is the only LIVE Japanese panel while the USD panel is frozen. The verb 'summary' is enhanced by concrete detail.

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 provides explicit when-to-use scenarios: 'what did the Japanese market do today?', 'is the dealer paying more or less for cards this week?', and before reasoning about any single Japanese card. It also mentions the per-card page as an alternative route, clarifying that this tool is for aggregate market data, not individual card details.

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