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temporal_query

Query code evolution over time to track changes, analyze trends, and compare metrics across specified time ranges.

Instructions

Query code evolution over time, track changes, and analyze trends

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityNoEntity ID or pattern to track (use "*" for all entities)*
metricNoMetric to track over time (required for trend analysis)
time_rangeYesTime range for the temporal analysis
analysis_typeNoType of temporal analysis (default: evolution)evolution
Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits, but it only mentions querying and analyzing, without addressing side effects, performance implications, or output characteristics. Critical transparency is missing.

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

Conciseness3/5

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

The single sentence is short but vague and inefficient; it lacks a front-loaded, informative structure. Could be more concise if it captured key details without being verbose.

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?

Given the complexity (4 parameters, nested objects, no output schema), the description is too brief. It omits expected return values, usage context, and relationships to sibling tools, leaving significant gaps for an AI agent.

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 description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; it merely repeats the general purpose, providing no extra value for parameter understanding.

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 queries code evolution and analyzes trends, providing a specific verb-resource combination. However, it does not differentiate from siblings like query_bi_temporal or advanced_query, limiting distinctiveness.

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 on when to use this tool versus alternatives such as advanced_query or analyze_architecture. The description lacks context for appropriate usage and exclusion criteria.

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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