Skip to main content
Glama

Autario

by com.autario
OverviewDiscussionsAdmin

pct_change

Read-onlyIdempotent

Period-over-period percentage change for an indicator. Use for growth rates (YoY, QoQ, MoM) | "how fast did German GDP grow", "what is US CPI doing month over month". Runs on any verified autario indicator (World Bank, FRED, Eurostat, OECD, IMF, WHO, ECB, US Census, SEC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNoReturn the full raw time series (heavy, many tokens). Default false → you get only the summary/stats, which is enough to ANSWER a question. Set true only when you must plot or export every point.
timeNo
entityYes
periodNoyoy | qoq | mom (default: yoy)
indicatorYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / full
      Added value: +{
+  "description": "Return the full raw time series (heavy, many tokens). Default false → you get only the summary/stats, which is enough to ANSWER a question. Set true only when you must plot or export every point.",
+  "type": "boolean"
+}
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the description does not need to repeat that. It adds useful scope context—'runs on any verified autario indicator'—but it does not disclose that by default only summary statistics are returned, which is a meaningful behavioral trait beyond the annotations.

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?

The description is compact, front-loaded with the core purpose, and uses examples efficiently. Every part adds value, and the pipe-separated examples make the usage pattern immediately understandable.

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 no output schema and several undocumented parameters, the description is incomplete for safe invocation from scratch. The `time` parameter is entirely unexplained, and the description does not describe what the output looks like or how much data is returned by default.

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 only 40%, so the description needed to compensate for the undocumented parameters (entity, time, indicator). It somewhat clarifies indicator scope but does not explain the `time` parameter at all, and entity is only implied by the example 'German GDP' rather than explicitly defined.

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 clearly states the tool computes period-over-period percentage change for an indicator, with concrete examples like YoY/QoQ/MoM growth rates. It is specific about the operation and resource, but it does not explicitly differentiate itself from sibling analytics tools like rolling_stats or lag_analysis.

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 description gives clear use cases ('Use for growth rates') and example queries ('how fast did German GDP grow'), which tells an agent when this tool is appropriate. It does not, however, name alternatives or state when NOT to use it.

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

All Autario toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources