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jrvalinas

elastic-mcp

by jrvalinas

Get Logs By Correlation Id

get_logs_by_correlation_id

Fetch all logs for a correlation, trace, or request ID to trace the full lifecycle of a request. Exclude matching noise like health checks with wildcard patterns.

Instructions

Fetch all logs for a correlation/trace/request id. Use exclude_messages to filter out logs matching wildcard patterns (e.g. ["/health", "heartbeat"]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
lastNo
limitNo
startNo
correlation_idYes
exclude_messagesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only mentions the exclude_messages filter and says 'Fetch all logs' – it doesn't state read-only status, side effects, pagination behavior, rate limits, or what happens if no logs are found. The output schema covers return structure, but behavioral traits beyond that are absent.

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 two concise sentences with no wasted words. The core purpose is front-loaded, and the second sentence adds a practical usage example for the filter. It's efficient and easy to parse.

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 6 parameters, 0% schema coverage, and no annotations, the description is far from complete. It only addresses one parameter and offers no context on time-range filtering, limits, or pagination. The presence of an output schema helps with return values, but input semantics remain largely undocumented, making the tool difficult to use correctly without external knowledge.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for all six parameters. It only explains exclude_messages with a concrete example. The remaining parameters (end, last, limit, start, correlation_id) are left entirely to the schema, which has no descriptions. This is inadequate for a 6-parameter tool.

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 'Fetch all logs for a correlation/trace/request id' – a specific verb, resource, and scope. It implicitly distinguishes from siblings like get_logs_for_service and get_latest_logs, though it doesn't explicitly name them. It's clear and actionable.

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

Usage Guidelines3/5

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

The description implies when to use it (when you have a correlation ID) but provides no explicit guidance on when not to use it or which sibling tool to choose instead. It doesn't mention alternatives or exclusions, leaving usage decisions to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.