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detect_anomalies

Detect anomalies in URL monitoring history by analyzing patterns of update frequency, performance, and content changes, providing severity scores to prioritize issues.

Instructions

Detect anomalies in URL monitoring history. Analyzes patterns to identify unusual update frequencies, performance degradation, or unexpected content changes. Returns anomalies with severity scores (normal/minor/moderate/critical) based on learned baselines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_severityNoMinimum severity level to include ('normal', 'minor', 'moderate', 'critical', default: 'moderate')moderate
daysNoNumber of days of history to analyze (default: 7)
Behavior3/5

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

No annotations provided, so description carries full burden. States it analyzes patterns and returns severity scores based on learned baselines, but does not disclose if it modifies data, requires specific permissions, or has side effects.

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?

Two sentences, front-loaded with action and result. No extraneous information; efficient and clear.

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?

No output schema, but description explains return values (severity scores). Lacks mention of read-only nature or prerequisites, but overall adequate for a simple detection tool.

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?

Input schema has 100% description coverage, providing clear parameter details. Description adds context about severity scores and analysis but does not significantly augment 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?

Clearly specifies detecting anomalies in URL monitoring history, analyzing patterns for unusual frequencies, performance degradation, or content changes. Distinguished from siblings as no other tool mentions 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 Guidelines2/5

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

No explicit guidance on when to use versus alternatives. Implies use for URL monitoring analysis but lacks contextual cues or exclusions.

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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