calculate_water_changeCalculate water change volume, weekly totals and dilution estimates.
| Name | Required | Description | Default |
|---|---|---|---|
| volume_liters | No | Tank volume or change volume in liters. | |
| change_percent | No | Percent of tank volume changed per water change. | |
| changes_per_week | No | Number of water changes per week. |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| tool | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / properties / generated_atRemoved value: -{
- "type": "string"
-}Output schema / requiredPrevious value: -[
- "data",
- "generated_at",
- "tool"
-]New value: +[
+ "data",
+ "tool"
+]Input schema / properties / change_percent / descriptionAdded value: +"Percent of tank volume changed per water change."Input schema / properties / changes_per_week / descriptionAdded value: +"Number of water changes per week."Input schema / properties / volume_liters / descriptionAdded value: +"Tank volume or change volume in liters."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds minimal behavioral context beyond stating the calculation outputs; it does not describe edge cases, assumptions, or limitations, but the annotation coverage lowers the burden.
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 directly conveys the tool's purpose with no redundant words. Every phrase adds value.
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 has an output schema and the description combined with full parameter descriptions provides enough context for a straightforward calculation tool. However, it lacks explicit guidance on how inputs relate to the three output types, which is a minor gap.
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?
All parameters have descriptive schema entries with ranges and units (e.g., volume_liters, change_percent, changes_per_week). The tool description does not add further parameter-specific meaning, so with 100% schema coverage, the baseline of 3 is appropriate.
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 verb ('Calculate') and resource ('water change volume, weekly totals and dilution estimates'), clearly distinguishing it from sibling tools like calculate_tank_volume or calculate_weekly_dose_totals.
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 implies usage for water change calculations but does not explicitly state when to use this tool over siblings or provide exclusions. The name and description make the use case clear, but no alternatives or when-not scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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