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

No annotations are provided, so the description must convey behavioral traits. It describes the aggregation behavior and data sources, but does not disclose side effects, permissions, or output format. Since it is a read-only summarization, the lack of explicit safety guarantees is a minor gap, but the description gives a clear functional behavior.

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 two sentences and front-loaded with the primary function, followed by usage context. No redundancy or filler; every clause contributes 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 tool has no output schema and no annotations, so the description is the sole source of context. It covers the tool's purpose, sources, and use cases, but omits expected output format or any limitations (e.g., data freshness, aggregation rules). This is adequate for simple use but leaves the agent guessing about the return value.

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?

All three parameters have schema descriptions (100% coverage), so the baseline is 3. The description adds only minimal context beyond the schema—it mentions 'scene' which aligns with scene_name, but does not elaborate on intent or limit semantics.

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 specifies the tool's function: 'demand_signals を要約する' (summarize demand signals) accumulated from two source tools, and explicitly lists the aggregation dimensions (scene, fit state, safety flags). This differentiates it from sibling tools like get_popular_products or find_product_gaps.

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 states when to use: 'どのシーン・どの fit 状態・どの安全フラグが多いかを把握したいときに呼ぶ' and lists concrete use cases (analysis, weekly reports, product planning prioritization). It does not explicitly mention alternatives or when not to use, so it lacks the exclusionary guidance for a 5.

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