DriftScope

compute_psi

Compute Population Stability Index (PSI) to evaluate feature shift severity between baseline and current CSV datasets. Accepts local paths or public URLs and a feature column.

Instructions

Computes Population Stability Index (PSI) to evaluate feature shift severity. Accepts both local file paths and public HTTP/HTTPS URLs.

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": {
      "baseline_csv": "<baseline_csv>",
      "current_csv": "<current_csv>",
      "feature_column": "<feature_column>"
    },
    "name": "compute_psi"
  }
}

Input Schema

Name	Required	Description	Default
`bins`	No
`current_csv`	Yes
`baseline_csv`	Yes
`feature_column`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 13, 2026

TDQS

B3/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that inputs may be local paths or public HTTP/HTTPS URLs, which is real context beyond the schema, but says nothing about return values, error behavior for unreachable URLs, or computational cost.

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?

Two short sentences, front-loaded with the core purpose and with no filler. Every clause earns its place.

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

Completeness2/5

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

A 4-parameter computation tool with no annotations, no output schema, and 0% schema description coverage needs far more: what the inputs must contain, what bins controls, and what the result looks like. The description leaves most of this unaddressed.

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

Parameters2/5

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

Schema coverage is 0% across 4 parameters, so the description must compensate. The file-path/URL hint partially explains the two CSV inputs, but baseline_csv, current_csv, feature_column, and especially bins (default 10) are never given meaning.

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

Purpose4/5

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

States a specific verb+resource ('Computes Population Stability Index') and its intent ('evaluate feature shift severity'). However, it never distinguishes itself from the close sibling check_feature_drift, which plausibly covers similar ground, so an agent cannot route between them from the description alone.

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

Usage Guidelines2/5

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

There is a soft usage cue ('evaluate feature shift severity') and input-source coverage, but no explicit when-to-use, when-not-to-use, or comparison against check_feature_drift/generate_mock_datasets. The agent is left to infer which drift tool applies.

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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