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Get Flow Logs

get_flow_logs
Read-only

Retrieve execution logs for an Appmixer flow and optionally filter them with an Apache Lucene query to diagnose runs and inspect message flow details.

Instructions

Get execution logs of an Appmixer flow. Optionally filter with an Apache Lucene query over fields such as "msg", "@timestamp", "portType", "port", "correlationId", "senderType", "senderId" and "inputMessages".

Input Schema

NameRequiredDescriptionDefault
idYesThe ID of the flow.
sizeNoMaximum number of log records to return.
queryNoApache Lucene query to filter the logs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.6/5.0
Behavior3/5

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

readOnlyHint=true already establishes this as a safe read, so the description's main added value is naming the Lucene-queryable fields. It says nothing about log ordering, retention window, or what a log record looks like, and gives no hint that results may be truncated — all relevant for a log-retrieval call.

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?

Two sentences, the operation stated first and the optional filter second. The field list is the only length, and it is load-bearing information rather than filler.

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

Completeness3/5

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

With no output schema, the description carries the burden of describing returns, and 'execution logs' plus a field list only partially covers that — record shape and ordering are left implicit. For a three-parameter read tool it is roughly adequate, but an agent cannot predict what it will get back.

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 the baseline is 3, but the description earns an extra point by enumerating concrete Lucene fields ('msg', '@timestamp', 'portType', 'port', 'correlationId', 'senderType', 'senderId', 'inputMessages') that the schema does not mention, making the query parameter materially more usable.

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?

States a specific verb and resource ('Get execution logs of an Appmixer flow'), which is meaningfully distinct from siblings like get_flow, get_flow_status and get_unprocessed_message. It does not explicitly name those siblings or contrast itself with them, so it stops short of a 5.

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 usage through 'Optionally filter with an Apache Lucene query', telling the agent when the query parameter is worth supplying, but it gives no guidance on when to reach for this tool versus get_flow_status or the unprocessed-message tools, and no exclusions.

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