stock_levelHow many units of a product you have on hand right now — search by product name or SKU. If this company uses Counter (the till), the figure is as at the last day-close: counter sales move stock once, when the day is closed, not at each scan.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description adds a non-obvious behavioral detail: counter sales do not decrement stock at the moment of sale, only at day-close. This is valuable context that prevents incorrect interpretation of the returned figure.
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?
Two sentences, both purposeful: the first states the result and accepted inputs, the second adds the important Counter timing caveat. The description is front-loaded, scannable, and contains no 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 one-parameter read-only lookup, the description is nearly complete: it explains what to search by, what the value represents, and when the value may be stale. It does not describe the exact output shape, but the phrase 'how many units' gives enough expectation for this tool's simplicity.
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?
With schema coverage at 0%, the description carries the full burden for explaining 'query.' It does so by stating that the query can be a product name or SKU, which is meaningful semantic guidance beyond the raw string 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 clearly identifies the tool as a current on-hand stock lookup, searchable by product name or SKU. It avoids ambiguity with sibling history/listing tools by emphasizing 'right now,' though it does not explicitly name an alternative.
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?
It gives practical search guidance ('search by product name or SKU') and explains an important timing condition for Counter users: stock reflects the last day-close. It stops short of contrasting with alternatives such as stock_movements or low_stock, so it is clear but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.