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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: PSL is returned in paise (with a note to convert to ₹) and the output includes a daily trendline. This helps the agent understand unit handling and output structure without contradicting the annotations.

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?

Two sentences: first lists the contents in a compact, front-loaded manner; second gives a single concrete use case. No wasted words, no repetition of schema details, and all information earns its place.

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?

Given the tool's complexity (multiple KPIs) and that an output schema exists, the description provides sufficient context: it names all major output components, flags the PSL unit conversion pitfall, and positions the tool as a headline/overview. This is complete for an overview tool, especially with a rich output schema to back it up.

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 description coverage is 100%—every parameter has a clear description in the schema, so the baseline is 3. The tool description does not add additional parameter semantics beyond listing high-level output fields (e.g., pincode coverage) that loosely relate to filters, but no new syntax or behavior is introduced. The schema already does the heavy lifting.

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 states the specific verb+resource: 'quick-commerce shelf-intelligence headline' and enumerates exact KPIs returned (OSA %, shelves & SKUs tracked, risk score, PSL, pincode coverage, trendline). This distinguishes it clearly from sibling overview tools like get_analytics_summary or get_dashboard_summary by naming its unique focus on availability and PSL.

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?

It provides an explicit use case: "Use for 'how is my quick-commerce availability'." This is clear contextual guidance. However, it does not mention when not to use it or name alternatives (e.g., get_shelf_availability for detailed shelf data), so it stops short of full exclusion/alternative guidance.

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