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

No annotations are provided, so the description carries the full burden. It fully discloses the computational method by printing the exact formulas (z × σ_d × √LT, reorder point, suggested restock), states that it is a pure calculation with zero fabrication, and lists its four return values. This makes the tool's behavior transparent without relying on structured 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 appropriately dense and well-organized: purpose statement, parameter list, return values, then formulas. It is lengthier than minimal, but every sentence carries information — estimation heuristics, defaults, context ranges — and the structure is logical. Slightly verbose but not bloated.

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 tool computes derived quantities, so the formula disclosures are the core behavioral contract and are fully specified. All 7 parameters are explained, defaults are noted, and the return fields are enumerated. The output schema flag is true, so return-value explanation is a bonus rather than a requirement. Nothing an agent needs to call it correctly is missing.

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%, so the description must compensate — and it does thoroughly. Every one of the 7 parameters is explained with units (件/天), practical estimation guidance (stddev can be estimated as 30% of daily sales if unknown), typical ranges (56–70 days China-to-FBA lead time), and the valid service-level values. This far exceeds what the bare schema provides.

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 precise statement of what the tool computes — safety stock, reorder point, and suggested restock quantity — using specific inventory formulas and explicitly asserting '零虚构' (no fabrication). The outputs are enumerated. It is clearly distinct from its siblings (fba_vs_fbm_decision, inventory_health_audit) by content, though it never names those alternatives explicitly.

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 never states when to use this tool versus the sibling tools, nor gives explicit exclusions. Usage context is only implied through the FBA lead-time hints and replenishment framing. An agent gets no direct guidance on choosing this over inventory_health_audit or fba_vs_fbm_decision.

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