radioactive_decayCalculate parent and daughter activities using NuDat 3 half-lives and branching. Supply an isotope ID, initial activity and elapsed time with units.
| Name | Required | Description | Default |
|---|---|---|---|
| target | No | Optional positive target activity, at most the initial activity. | |
| elapsed | Yes | Elapsed time. | |
| initial | Yes | Initial activity. | |
| isotope | Yes | Isotope ID, e.g. mo99. | |
| time_unit | Yes | s, min, h, d or y. | |
| activity_unit | Yes | Activity unit, e.g. Bq or Ci. |
Changes observed during successful MCP inspections.
Input schema / properties / targetAdded value: +{
+ "description": "Optional positive target activity, at most the initial activity.",
+ "type": "number"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
It reveals critical behavioral traits beyond the structured data by specifying that the calculation uses 'NuDat 3 half-lives and branching.' This informs the user that the calculation is based on a specific, established scientific model, which is more valuable than merely saying 'calculates decay.'
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 tool definition is a single, highly dense sentence where every clause serves a critical purpose. There is zero fluff, making it maximally concise and effective.
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?
Given that the input schema is complete and the calculation method is stated, the description fully equips the agent to understand exactly what the tool performs and what inputs it requires without needing external documentation.
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 100% schema description coverage, the baseline for this score is 3. The description provides functional context to the parameters (e.g., 'supply an isotope ID' instead of just 'isotope'), but does not add novel meaning beyond what the detailed schema already 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 is highly specific, using the verb 'Calculate' in the context of 'parent and daughter activities.' It clearly defines the scope of the physics calculation using NuDat 3 methodology.
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 clearly dictates the necessary inputs required for the calculation (isotope ID, initial activity, and time units). While it does not explicitly compare itself to other complex physics tools, it sets a clear functional boundary for its usage.
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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