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jaeger_compare_windows

Read-onlyIdempotent

Detect performance changes by comparing trace aggregates between two time windows for a service, showing per-operation latency and error rate differences.

Instructions

Compare aggregate trace behavior between two time periods for a service.

Fetches traces from both time windows, aggregates span statistics per operation, then compares the aggregate behavior to detect performance changes.

Examples: - Use when: "Did our latest deployment affect performance?" → compare pre-deploy and post-deploy time windows for the service. - Use when: "Which operations got slower after the database upgrade?" → check the comparison_p95_us and p95_delta_pct columns for increases. - Use when: "Are we seeing new error patterns?" → look for operations with increased error_rate_delta. - Use when: "Did we add or remove any API endpoints?" → check added_count and removed_count in the summary. - Don't use when: You want to compare two specific traces (use jaeger_compare_traces instead). - Don't use when: You want full span detail for a single trace (use jaeger_get_trace instead).

Returns: WindowComparisonOutput with per-operation diffs and summary statistics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum traces to fetch per window (default 100).
serviceYesService name to compare across time windows.
operationNoOptional operation name filter.
baseline_endYesBaseline window end time (Unix timestamp in microseconds).
baseline_startYesBaseline window start time (Unix timestamp in microseconds).
comparison_endYesComparison window end time (Unix timestamp in microseconds).
comparison_startYesComparison window start time (Unix timestamp in microseconds).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYes
operationsYes
added_countYes
baseline_endYes
faster_countYes
slower_countYes
removed_countYes
baseline_startYes
comparison_endYes
comparison_startYes
total_operationsYes
overall_deviation_scoreYes
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context about fetching traces, aggregating per operation, and comparing, without contradiction.

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?

Well-structured: purpose sentence, what it does, bullet-pointed usage scenarios, and exclusions. Front-loaded and concise.

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

Completeness5/5

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

Given 7 params (5 required), 100% schema coverage, output schema present, and rich annotations, the description covers all necessary context without gaps.

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 100%, so baseline is 3. The description adds meaning through usage examples that implicitly reference parameters (e.g., pre/post-deploy windows), though it doesn't describe each parameter explicitly.

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 clearly states the tool's purpose: compare aggregate trace behavior between two time periods for a service. It uses specific verbs and distinguishes from siblings like jaeger_compare_traces and jaeger_get_trace.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

Explicitly provides when to use (e.g., deployment impact, database upgrade) and when not to use (specific trace comparison, full span detail), with alternative sibling tools mentioned.

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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