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Kalmantic

PeakInfer MCP Server

by Kalmantic

compare_to_baseline

Compare current analysis results to a historical baseline to detect drift, uncover performance regressions, and validate optimization improvements.

Instructions

Compare current analysis results to a historical baseline

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseline_pathNoPath to baseline JSON file
current_analysisYesCurrent analysis results (InferenceMap format)
Behavior2/5

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

With no annotations, the description carries full burden but only states the high-level action. It does not disclose whether the tool is read-only, how it handles a missing baseline_path, or what the comparison result looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no wasted words. It is concise but could arguably benefit from a second sentence to clarify the return value, yet it remains appropriately sized.

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

Completeness2/5

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

For a tool with no output schema and no annotations, the description is too sparse to understand the tool's behavior fully. It does not explain the return format, failure modes, or how the comparison is performed, making it incomplete for an AI agent to invoke correctly.

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 covers both parameters with descriptions (100% coverage). The description in the tool does not add extra syntax or format details, but it does align the two parameters with the concepts of 'current analysis' and 'baseline', so it meets the 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 a specific action ('Compare') with two resources: current analysis results and a historical baseline. This distinguishes it from sibling tools like analyze or save_analysis, though it lacks detail on the comparison output.

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 guidance is provided about when to use this tool vs. alternatives. It does not specify prerequisites (e.g., baseline must exist) or when to prefer it over analyze/save_analysis.

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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