Skip to main content
Glama

fluid_target

Rough daily fluid estimate from body weight (about 30-35 ml/kg), framed against the NHS 6-to-8-glasses guidance. Needs rise in heat, with exercise, and with GLP-1 sickness. A general estimate, not a medical fluid target.

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": {
      "weight_kg": "<weight_kg>"
    },
    "name": "fluid_target"
  }
}

Input Schema

NameRequiredDescriptionDefault
weight_kgYesBody weight in kg (30-350)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations present, the description carries the full disclosure burden and does so credibly: it reveals the underlying formula, the NHS comparison frame, the adjustment drivers, and an explicit scope limit ('general estimate, not a medical fluid target'). It does not say what units or shape the result takes, which is the only notable gap for a pure calculation.

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?

Three tight sentences: purpose and formula first, then the modifiers, then the disclaimer. Every clause adds information and nothing is repeated from the schema.

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?

For a single-parameter, annotation-free calculation with no output schema, the description covers basis, framing, adjustment factors, and limits. The one thing an agent might still want is the unit and rough magnitude of the returned estimate.

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

Parameters4/5

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

Schema coverage is 100% and there is only one parameter, so the baseline is already 3. The description adds real meaning beyond the schema by explaining that weight is transformed through a 30-35 ml/kg ratio, telling the agent how the input drives the output rather than merely what to supply.

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 opens with a specific verb and resource: 'Rough daily fluid estimate from body weight', plus the actual ratio (30-35 ml/kg). That is enough for an agent to distinguish it from siblings such as protein_target, bmi_check, and energy_tdee without opening any schema.

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

Usage Guidelines3/5

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

The description gives implied usage context — heat, exercise, and GLP-1 sickness all raise needs — but never says when to choose this tool over an alternative or when it does not apply beyond 'not a medical fluid target'. The guidance is suggestive rather than prescriptive.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources