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Glama

descriptives

Compute summary statistics (N, missing, mean, SD, SE, min, Q1, median, Q3, max, sum) from source files via STATISTICA COM, honoring declared missing codes.

Instructions

Fast descriptive statistics computed in Node from data read through COM (N, missing, mean, sd, se, min, q1, median, q3, max, sum). Missing values are honoured using each variable's declared missing code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path to the source file.
sheetNo
attachNoAttach to the already-running STATISTICA instance and edit it live (no new process, the app is not closed).
variablesNoSubset to report on.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.3.0

TDQS

B3.1/5.0
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 missing values are honoured using declared missing codes and that computation happens in Node via COM, but it does not state whether the operation is read-only, what permissions are needed, or whether any file mutation occurs.

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 tightly written sentences with no wasted words. The core purpose and output statistics are front-loaded, followed by the important missing-value handling detail.

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

Completeness3/5

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

The description lists the statistics returned and explains missing-value handling, which is helpful given there is no output schema. However, it omits any usage guidance relative to siblings and does not clarify the sheet or attach parameters, leaving meaningful gaps for an agent choosing among many analysis tools.

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 description coverage is 75%, which is not high enough to assume the schema fully compensates. The description adds no parameter-specific meaning: it does not clarify the sheet parameter (undocumented in schema), nor does it explain how attach or variables affect behavior beyond what the schema already states.

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?

The description states a specific verb+resource: computes descriptive statistics from data read through COM, and lists the exact statistics returned. It is clear about what the tool does, but it does not differentiate itself from the sibling statistica_descriptives tool, which likely has overlapping purpose.

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 no explicit guidance on when to use this tool versus alternatives such as statistica_descriptives or describe_spreadsheet. Usage is only implied by the tool name and output list, leaving the agent to infer the appropriate context.

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