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

With no annotations, the description carries the behavioral burden and does add useful context by defining the SPP formula and the output framing (was, became, difference in pp). However, it does not disclose whether the tool is read-only, how the optional group parameter affects behavior, or any limitations.

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?

Three compact sentences, each earning its place: the core answer, the formula, and the trigger phrases. The most important context is front-loaded with no wasted words.

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 formula and usage triggers are helpful, and an output schema is present, but the single optional parameter is completely undocumented. Without annotations, the description also leaves assumptions about side effects and read-only behavior unstated, so correct invocation is not fully supported.

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 0% and the description never mentions the only parameter, `group`. The agent has no information about what group means, how it filters results, or what values are acceptable, so the description adds nothing to parameter understanding.

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 exactly what the tool reports — where the regular-customer discount shifted, with was/became/difference in percentage points — and defines SPP via formula. It is specific enough to distinguish it from siblings like parsee_price_history or parsee_compare_diff.

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?

Explicit usage triggers are provided: use when the user asks 'where the discount dropped' or 'what changed in SPP'. It gives clear context for when to call the tool, though it does not name alternative tools or state when not to use it.

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