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

No annotations are provided, so the description carries the full behavioral burden and does so well: it discloses the composite score range (0-100), the sort order (attentionScore descending), the default filter behavior (minAttentionScore default 0), the default analysis scope (top 50 by sales over 30 days), and the presence of a `flags` array explaining the score. This is unusually rich behavioral disclosure for a no-annotation tool.

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 with the core capability in all-caps, followed by use-case quotes, then mechanism, then return shape, then parameters. Some redundancy ('which products need fixing?' / 'are there any product issues?' / 'which products are performing badly?') but each adds a slightly different nuance. Slightly dense but well organized.

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 6-parameter, no-output-schema synthesis tool with no annotations, the description covers purpose, when-to-use, return shape (signals + flags), sorting, filtering defaults, and scope defaults. An agent has everything needed to invoke it correctly and interpret the result.

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?

Schema coverage is already 100%, so the schema documents limit, store, _offset, endDate, startDate, and minAttentionScore. The description still adds value by explaining the semantics behind minAttentionScore (set to 30 to see only flagged products) and the default window (top 50 by sales over last 30 days), which reinforces rather than merely repeats the schema.

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+resource ('CROSS-SOURCE PRODUCT HEALTH SCAN' returning per-product reviews + refunds + sales velocity + inventory + composite score) and explicitly distinguishes itself from siblings like get_top_products, get_refunds, get_reviews, get_inventory by naming them as what it replaces. An agent can immediately tell this is a synthesis tool vs. the individual-data siblings.

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?

Gives explicit when-to-use trigger phrases ('which products need fixing?', 'what should I look at?') and names the alternative path (stitching the sibling tools manually) that this replaces. The rationale (consistent synthesis, same heuristic) makes the value proposition concrete.

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