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

Well beyond the annotation set, it discloses data provenance and staleness (initial load, hourly worker, post-webhook sync), privacy behavior (customer_hash instead of buyer data), exclusion rules in daily_sales, and the customers_rfm caveat that only orders with a customer_hash appear and that the days window filters on the last order. This is exactly the operational context an agent cannot get from readOnlyHint/destructiveHint alone.

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-loads the most important fact (READ-ONLY, HISTORY) and has zero filler, but the single dense paragraph with embedded parentheticals is hard to scan for a seven-view tool; a bulleted view list would preserve the information and improve structure.

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 and no annotations carrying semantics, the description does the heavy lifting well: it covers provenance, views, exclusions, privacy and windowing. It omits return shape per view beyond a brief hint and says nothing about pagination/ordering with `limit`, which is the remaining gap for a query tool.

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 100%, so the baseline is 3; the description adds real value by explaining that `days` scopes stock/orders/daily_sales and, non-obviously, that for customers_rfm it filters on the last order date. View semantics are richly explained. It stops short of discussing `limit`/ordering behavior, so not a 5.

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 (read-only history query against the Vendooly data-hub) and enumerates the seven selectable views with concrete contents (products with SKU/EAN/price/stock, daily_sales excluding cancelled/failed/refunded, etc.). It explicitly separates itself from the live `woo_*` tool family, so an agent can place it in the toolset without opening the schema.

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 an explicit routing rule: use this for trends and history, use the live `woo_*` tools for current store state. Each view description further implies the correct selection (e.g. customers_rfm for RFM, sync_status for freshness), leaving little to inference.

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