detect_dead_slow_stock

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains that the tool analyzes a period, applies thresholds for dead and slow stock, and reports tied-up inventory value. It implies a read-only analytical operation through 'Identify,' and gives the key decision-oriented output. It could mention how results are grouped or returned, but it is not misleading.

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 a single, front-loaded sentence that defines the core behavior, then adds the decision context. Every phrase contributes: the detection criterion, the slow/good threshold, and the output value. There is no redundancy or filler.

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 simple tool with two optional parameters and no required fields, the description plus schema is sufficient for an agent to invoke it correctly. It explains what the analysis identifies and what value it reports. The absence of an output schema is a minor gap, but the description names the core return concept (tied-up inventory value), and the tool complexity is low.

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%, so the parameters are already well-documented in the schema. The description adds minimal extra meaning beyond referencing 'period' and 'average demand,' which maps to deadDays and slowFactor. Baseline 3 applies because the schema 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 names a specific verb ('Identify'), a clear resource ('dead stock and slow-moving stock'), and precise definitions for each category (zero demand, demand < slowFactor × average). It also mentions tied-up inventory value as an output, which makes it clearly distinct from related siblings like predict_stockout or get_total_stock.

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 gives an explicit intended use case: 'Helps prioritise clearance or write-off decisions.' This provides clear context for when to apply the tool among the many inventory-related siblings. It does not name alternatives or state when not to use it, but the purpose is specific enough to disambiguate.

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