GoAI Moat Cross-Border Inventory & Fulfillment

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

With no annotations provided, the description carries the full disclosure burden, and it does well: it openly states this is a decision framework, not a real-time fee calculator (managing expectations about precision), and it enumerates the output contract (FBA/FBM scores + recommendation + trade-off reasons + applicable scenarios). This is meaningful behavioral context beyond the bare schema, though it does not discuss edge cases or any prerequisites.

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?

Well-structured: purpose is front-loaded in the first line, followed by a compact one-line-per-parameter list, ending with a single return summary. Every line earns its place. It is necessarily long because it carries all parameter semantics at 0% schema coverage, but the formatting keeps it scannable and parceled.

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 9-parameter decision tool, the description covers purpose, parameter semantics, and the output contract at a high level. Since an output schema exists, the lack of deep detail on return-value formatting is acceptable. The primary gap is the absence of usage guidance versus siblings and any mention of scoring methodology or indeterminate-output edge cases, but overall it is well-rounded for its complexity.

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 fully compensate, and it does. All 9 parameters are documented with units, business meaning, and rationale: unit_weight_lb in pounds, is_heavy flagged as '>20 lb, FBA fees jump by weight bracket', margin_pct explained as gross margin '% to judge ability to absorb FBA fees', prime_sensitive tied to standard/homogeneous products, and lead_time_days linked to FBM self-delivery competitiveness. This adds far more than the bare type/default schema.

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 first line states a specific resource (FBA vs FBM) and a precise purpose: multi-dimensional scoring + recommendation + applicable scenarios + cost trade-offs. It distinguishes itself from siblings by declaring it is a decision framework and explicitly '不做实时费率' (not real-time rates), which sets it apart from inventory audit and safety-stock planning tools.

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 purpose implies the usage context (choose between FBA and FBM fulfillment), and the '不做实时费率' parenthetical hints at one exclusion. However, there is no explicit statement of when to use it vs the sibling tools (inventory_health_audit, safety_stock_reorder_plan), no 'use when...' phrasing, and no explicit alternatives mentioned. Usage is implied rather than spelled out.

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

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

With no annotations provided, the description carries the transparency burden. It discloses the return composition (“四维风险 + 综合风险等级 + 行动清单”), the 181-day long-term-storage threshold, and the modeled consequences for hero ASINs. It stops short of explicitly stating that the tool is read-only and does not execute the recommended removal/discount/replenishment actions, though “返回” strongly implies this.

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 high-value purpose is front-loaded, followed by a compact bullet list of parameters and a single line for the output. Every sentence earns its place, and there is no filler or repeated schema information.

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 7-parameter risk-calculation tool with no annotations, the description covers all input semantics, key business rules, and the output shape, while the existing output schema handles formal return-field details. Nothing essential to invoking and interpreting the call 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 explain the parameters itself. It does so for all seven parameters, including units (“件/天”), business meaning (“当前在库数量”), the 181-day trigger for days_in_storage, USD and optionality for unit_cost, and the behavioral impact of is_hero_asin. This fully compensates for the empty schema.

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 a specific task—“库存健康四维审计”—and names the exact dimensions evaluated (断货风险/超储/周转/IPI) plus the concrete output (风险等级 + 行动清单). This clearly identifies what the tool does, but it does not explicitly distinguish itself from sibling tools like safety_stock_reorder_plan or fba_vs_fbm_decision.

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 intended scenario is implied by the first line: use it when an inventory-health audit across the four dimensions is needed. However, there is no explicit statement of when to prefer this tool over fba_vs_fbm_decision or safety_stock_reorder_plan, and no exclusions or alternative-routing guidance.

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

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.