Skip to main content
Glama
Sign In
CERN ROOT MCP Server

CERN ROOT MCP Server

by MohamedElashri
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_branch_stats

Read-onlyIdempotent

Compute statistics for branches in a CERN ROOT tree, including derived variables defined by expressions and optional cut selection, to inspect data distributions before analysis.

Instructions

Get statistics for branches (supports derived variables via defines)

Input Schema

NameRequiredDescriptionDefault
pathYesFile path
definesNoDerived variable definitions (dict of name: expression)
branchesYes
selectionNoOptional cut expression
tree_nameYesTree name

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.3.1
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / branches / minItems
      Added value: +1
  2. First observedv0.1.7

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description adds only that derived variables are supported via defines, but says nothing about what statistics are computed, the return shape, or any error conditions.

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?

The single sentence is front-loaded and free of filler. It is efficient, though the parenthetical is the only extra detail provided.

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?

With five parameters, a nested defines object, and no output schema, the description is too thin to explain what statistics are returned or how defines, selection, and tree_name interact. It leaves significant gaps for a tool of this complexity.

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 80%, so the schema already documents most parameters. The description's mention of derived variables via defines largely restates the schema and adds no new meaning about selection, tree_name, or path.

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 and resource: 'Get statistics for branches.' It is clear what the tool returns at a high level, but it does not distinguish itself from sibling tools such as list_branches or read_branches.

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 guidance on when to use this tool instead of list_branches or read_branches, and no prerequisites or exclusions are mentioned. The only implied usage is that it computes statistics rather than listing branches.

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

Deploy Server

Other Tools