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oaslananka
by oaslananka

Record Baseline

record_baseline

Capture current system metrics during healthy operation to establish a performance baseline, enabling more accurate anomaly detection during incident analysis.

Instructions

Record current metrics as baseline during normal operation for more accurate anomaly detection later

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelNoLabel for this baseline (e.g. "normal", "peak-hours")default
connectionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostYes
labelYes
savedYes
messageYes
warningsYes
sample_countYes
Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, so the write nature is implied but not explicitly detailed. The description adds the behavioral context of running during normal operation and the purpose for future anomaly detection, but does not disclose whether baselines are overwritten or how they are stored.

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 a single, information-dense sentence. It front-loads the action and purpose without any wasted words, achieving high conciseness while remaining 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?

The tool has a nested connection object and an output schema, and the description provides adequate context for its use. It covers the main purpose and when to use it, though it could mention the SSH connection mechanism or how it fits with sibling tools like 'compare_to_baseline' for fuller completeness.

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?

The schema provides descriptions for the 'label' parameter and nested connection properties, covering 50% of parameters. The description adds no parameter-specific information, but the schema already conveys meanings, resulting in a neutral baseline.

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 records current metrics as a baseline for anomaly detection. It uses a specific verb and resource, and the phrase 'as baseline' distinguishes it from generic snapshots, though it doesn't explicitly differentiate from the sibling 'snapshot' tool.

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 specifies that it should be used 'during normal operation' for more accurate anomaly detection later, providing clear usage context. However, it does not mention when not to use it or what alternatives might be preferred, such as 'snapshot' for point-in-time captures.

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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