Skip to main content
Glama
natejswenson

local-budget

by natejswenson

find_anomalies

Detect transactions exceeding a merchant's historical average by a configurable standard deviation threshold. Scope results by month and limit to focus on recent anomalies.

Instructions

Transactions far above their merchant's historical mean (default 2 sd). UNSCOPED by default — returns flags across ~2 years of history; pass month (YYYY-MM) and/or limit to scope the output (detection baselines still use full history).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
monthNo
sd_thresholdNo
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the default threshold (2 sd), the ~2-year history window, and the important nuance that detection baselines always use full history even when scoped. It lacks explicit mention of read-only status or return format, but covers key behavioral traits.

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 two sentences, front-loads the core definition, and efficiently packs scoping and baseline behavior without redundancy. Every sentence adds value.

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?

Given the absence of annotations and output schema, the description covers detection logic, default scope, and parameter usage well. However, it does not describe the structure of the returned 'flags' or any additional caveats. This is a minor gap for a moderately complex find tool.

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

Parameters4/5

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

The input schema provides zero descriptions (0% coverage), so the description must compensate. It explains month (format and scoping), limit (scoping), and implies sd_threshold's role via the default. The exact effect of limit is under-specified, but overall the parameters gain meaningful context.

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?

The description clearly defines the tool's function with a specific detection criterion (transactions above merchant historical mean by standard deviation). It distinguishes itself from sibling query/breakdown tools by focusing on anomaly detection, and the phrase 'returns flags' provides a concrete action.

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 explains the default unscoped behavior and explicitly instructs how to scope using month and limit, including the month format. It stops short of naming alternative tools or stating when not to use it, but the usage context is clear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/natejswenson/local-budget'

If you have feedback or need assistance with the MCP directory API, please join our Discord server