MPStats Item Analytics

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

The description extensively discloses behavior beyond the annotations: rolling averages, per-day graph semantics, zero-cell meaning, auth failure modes, and a full error taxonomy. It also clarifies missing values are None, never 0, which is a subtle but crucial behavioral detail. No contradictions with the read-only/idempotent 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?

The description is well-structured with clear sections (overview, return format, error format) and every sentence carries meaningful information. It is length-appropriate for the tool's complexity and front-loads the core purpose.

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?

Despite the tool's moderate complexity, the description covers the full usage context: what the tool returns, the exact structure, all error cases, and prerequisites. The output schema and annotations are supplemented effectively, leaving little room for agent confusion.

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?

The schema already has 100% coverage with detailed parameter descriptions, so the baseline is 3. The tool description adds useful context about what the data represents (e.g., 'per-SKU', '30-day') but does not add significant new meaning beyond the schema's parameter descriptions.

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 opens with a specific, actionable verb ('Fetch') and identifies both the resource (MPStats) and scope (per-SKU 30-day sales analytics, Ozon or Wildberries). It clearly distinguishes this from sibling tools via the per-SKU granularity and explicit marketplace focus.

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?

The description clearly establishes when to use the tool: for per-SKU analytics on MPStats data. It also gives a key prerequisite (MPSTATS_MP_AUTH env var). However, it does not explicitly state when NOT to use this tool or name an alternative, so it falls short of a 5.

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