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chaandannn

nable (finops-mcp)

get_anomalies

Retrieve unacknowledged cost anomalies identified from historical baselines, with optional filtering by provider, severity, limit, and account.

Instructions

Return active (unacknowledged) cost anomalies detected from historical baselines.

Args: provider: Filter to a specific provider. None = all. severity: "high", "medium", or "low". None = all severities. limit: Max anomalies to return (default 20). account: Named AWS account from accounts.yaml to filter results.

Examples: - "Are there any cost anomalies I should know about?" - "Show me high-severity cost spikes" - "What spiked in AWS this week?" - "Any anomalies in the production account?"

Note: Anomalies require at least 7 days of snapshot history. Run 'finops snapshot' or wait for the daily job to accumulate data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
accountNo
providerNo
severityNo
Behavior3/5

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

With no annotations, the description must disclose behavior. It correctly notes the prerequisite (7 days of snapshot history) and implies it is a read-only operation ('return'). It does not mention any destructive behavior, but also lacks details on rate limits or authentication needs.

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 concise and well-structured: first sentence defines purpose, followed by parameter documentation, examples, and a note. No unnecessary words.

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?

For a 4-parameter tool with no annotations and no output schema, the description covers purpose, each parameter, usage examples, and a prerequisite. It does not explain return format, but that's acceptable without output schema. Overall, it provides sufficient context for correct agent usage.

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?

Schema coverage is 0%, so the description adds significant value by explaining each parameter (e.g., 'Filter to a specific provider. None = all.') and providing the default for limit. This goes beyond the bare schema.

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 states the tool returns 'active (unacknowledged) cost anomalies', using a specific verb and resource. It clearly distinguishes from siblings like 'acknowledge_anomaly' (different action) and 'get_account_anomalies' (likely filtered by account).

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?

Examples show when to use (e.g., 'Are there any cost anomalies...'), and the note about requiring 7 days of history provides context. However, it does not explicitly state when to avoid this tool or compare to siblings like 'get_account_anomalies'.

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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