nds-mcp

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nds_get_q_value

Get nuclear Q-values from AME2020 for specified Z and A. Covers alpha, beta, and other decay modes with precise energy release data.

Instructions

Get Q-values from AME2020: Qα, Q(2β⁻), Q(εp), Q(β⁻n), Q(4β⁻), Q(d,α), Q(p,α), Q(n,α).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "Z": "<Z>",
      "A": "<A>"
    },
    "name": "nds_get_q_value"
  }
}

Input Schema

Name	Required	Description
`A`	Yes	Mass number
`Z`	Yes	Atomic number
`type`	No	Q-value type (omit for all)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Aug 9, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, and the description indicates a read operation (Get) with a data source (AME2020). It does not disclose output format, default behavior when 'type' is omitted, or error handling, but the low-risk nature of a query tool keeps it at a mid-level score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence stating the action and listing the Q-value types. No filler words, every element is informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (3 parameters, no output schema), the description covers the essential purpose and differentiates from siblings. It could mention that omitting 'type' returns all Q-values, but that is already captured in the schema, so the context is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all parameters (Z, A, type) are already documented. The description adds human-readable Q-value notation (e.g., Q(2β⁻)) that maps to enum values, but this is marginal beyond the schema's own 'Q-value type (omit for all)' description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Get' with the resource 'Q-values from AME2020', and explicitly lists the available Q-value types, clearly distinguishing this from sibling tools like nds_get_mass and nds_get_separation_energy.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies usage when Q-values are needed and lists all types, but it does not explicitly mention when not to use it or name alternatives. This provides clear context without exclusions, earning a 4.

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