TeamPredict HR Calculators

Employee Net Promoter Score (eNPS)

enps_score

Read-onlyIdempotent

Calculate an employee Net Promoter Score (eNPS) from survey response counts: the percentage of promoters minus the percentage of detractors, from -100 to +100. Use it when you have the count of people who answered 9-10 (promoters), 7-8 (passives) and 0-6 (detractors) to the question 'How likely are you to recommend working here?'. Returns the score, both percentages and a rule-of-thumb reading (not a universal benchmark).

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": {
      "promoters": "<promoters>",
      "passives": "<passives>",
      "detractors": "<detractors>"
    },
    "name": "enps_score"
  }
}

Input Schema

Name	Required	Description
`passives`	Yes	Number of responses scoring 7 or 8.
`promoters`	Yes	Number of responses scoring 9 or 10.
`detractors`	Yes	Number of responses scoring 0 to 6.

Output Schema

Name	Required	Description
`inputs`	Yes	The inputs as used, with defaults filled in.
`results`	Yes	The computed numbers. Unavailable numbers are null.
`summary`	Yes	One or two plain sentences with the headline numbers.
`calculator_url`	Yes	The TeamPredict calculator page that shows the same calculation, where a person can change the inputs.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 25, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, so the bar is lower; the description adds real context by disclosing the output shape (score, percentages, rule-of-thumb band) and cautioning that the reading is not a universal benchmark. It does not state behavior for a zero-response input (division by zero), which would be the remaining useful disclosure for a computation tool.

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

Conciseness4/5

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

Two sentences, front-loaded with the calculation and scope, then the usage condition. Minor internal redundancy in restating 'eNPS' and the promoter/detractor definition, but no filler.

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?

Covers inputs, formula, output range and interpretation caveat for a simple three-integer tool, and an output schema exists so return values needn't be explained. Missing only edge-case handling description (all-zero counts), which keeps it from a 5.

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% and each parameter already documents its 0-6 / 7-8 / 9-10 bucket, so the baseline is 3. The description restates those same bucket mappings rather than adding new semantics such as whether non-integer or negative counts are rejected.

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?

States a specific verb (Calculate) plus the resource (eNPS) and spells out the exact formula (percentage of promoters minus percentage of detractors) and output range (-100 to +100). This clearly distinguishes it from the payroll/date siblings, which involve no survey math.

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 'Use it when you have the count of people who answered 9-10 / 7-8 / 0-6' clause gives explicit triggering conditions, including the exact survey question context. It stops short of stating when NOT to use it (e.g., if you hold raw per-respondent scores rather than counts), so no full alternative routing.

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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