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

With no annotations at all, the description carries the full disclosure burden. The framing ('stats collected through Kaupia') implies a read-only aggregate, and the presence of an output schema covers the return shape, but nothing states scope (all shops vs one shop), time window, freshness, or permissions.

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?

A single tight sentence with the most informative element ('per-shop outcome stats') front-loaded and no filler. It is efficient but so terse that useful scope details are omitted rather than wastefully stated.

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 read with an output schema, the description covers what the data represents, which is the main thing needed. It is still thin on aggregation scope and timeframe, which matters for interpreting a scorecard.

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?

Zero parameters, so the baseline is 4 and there is no schema semantics to add. The only mild gap is that the name implies per-shop data yet the tool accepts no shop identifier, leaving the caller to wonder how shop scoping is applied.

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 names a specific resource — per-shop outcome stats, split into delivered vs problems — sourced from Kaupia, which is enough to distinguish it from report_outcome (which writes outcomes) and search_products. It lacks an explicit verb, so an agent must infer this is a retrieval tool rather than a reporting endpoint.

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?

No guidance on when to call this versus report_outcome, or versus any product-discovery sibling. The reader has to guess whether scorecards are fetched before or after reporting outcomes, and there is no stated prerequisite for data to exist.

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