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alexpota

cloudscope-mcp

Detect Cost Anomalies

detect_anomalies
Read-onlyIdempotent

Identifies unexpected cloud cost increases by comparing recent daily spending against a prior period. Returns services with cost spikes sorted by increase amount.

Instructions

Compares daily spending over the last N days against the prior N days to find cost spikes. Returns a list of services where spending increased above the threshold percentage, sorted by increase amount. Each entry includes service name, previous cost, current cost, percentage change, and absolute change in USD. Returns an empty list if no anomalies found. Use this when the user asks about unexpected cost increases, billing surprises, or wants to know if anything changed recently.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoCloud provider to query (azure or gcp)azure
daysNoNumber of days to compare (default: 7)
thresholdNoMinimum percentage increase to flag (default: 20)
Behavior4/5

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

The description explains the comparison logic, sorting, and that it returns an empty list if no anomalies. Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds context about the output structure but not about rate limits or prerequisites.

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?

Four sentences, no fluff, front-loaded with the main action. Every sentence adds value.

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

Completeness5/5

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

Given the tool's simplicity (3 optional params, no output schema), the description covers what it does, what it returns, and when to use it. No missing information.

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 coverage is 100% with clear descriptions for all parameters. The description does not add extra parameter details beyond the schema, but it contextually explains how days is used for both periods. Baseline 3 is appropriate.

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 states the tool compares daily spending to find cost spikes, lists the output fields, and distinguishes its purpose from siblings like compare_periods by focusing on anomaly detection.

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

Usage Guidelines5/5

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

The description explicitly tells when to use the tool: when the user asks about unexpected cost increases, billing surprises, or recent changes.

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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