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system_events

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Monitor Docker daemon events in real time. Apply filters for specific event types, set a limit on events returned, or cap the wait time with a timeout.

Instructions

Stream real-time events from the Docker server, bounded by limit events or timeout_seconds.

Returns when limit events are collected or timeout_seconds elapses, whichever comes first (limit caps memory; timeout_seconds caps how long the call blocks — without it a quiet daemon would block indefinitely, since the stream only yields on an actual event).

Caveat for ssh:// daemons: docker-py can't cancel an SSH stream, so the timeout_seconds watchdog can't interrupt a fully idle stream — bound with until/limit (or a non-SSH endpoint).

"Wait for the next matching event" idiom: pass limit=1 with filters narrowed to what you care about (e.g. {"type": "container", "event": "health_status"}) and a generous timeout_seconds. This blocks until that one event arrives (or the timeout elapses, returning an empty list) instead of re-polling a snapshot on a timer — there's no separate wait tool for this since the filtering this call already does covers it.

args: since - Show events created since this timestamp until - Show events created until this timestamp filters - Filters to apply to the event stream limit - Max events to return (default 100) timeout_seconds - Max wall-clock seconds before returning what was collected (default 30) returns: list - A list of decoded event dicts (length <= limit)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sinceNo
untilNo
filtersNo
timeout_secondsNo
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral details: blocking behavior, the fact that the call returns when limit or timeout is reached, the SSH caveat, and the return format. This goes beyond the annotations.

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 well-structured with paragraphs, a list of parameters, and a return type. It is detailed but not overly verbose. Minor redundancy could be trimmed, but it earns its length.

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 5 parameters, no required parameters, and no output schema, the description covers all necessary aspects: behavior, parameter meanings, return type, and edge cases. It is complete for an agent to use correctly.

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

Parameters5/5

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

The input schema has 0% description coverage, so the description carries the full burden. It explains each parameter (since, until, filters, limit, timeout_seconds) with clear semantics and default values, adding significant meaning beyond the schema.

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 it streams real-time events from the Docker server, bounded by `limit` or `timeout_seconds`. It is specific about the resource (Docker events) and action (stream), and distinguishes from sibling tools by explaining the 'wait for next event' idiom, which is unique among the many monitoring tools.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use the tool, including the 'wait for the next matching event' idiom and caveats for SSH daemons. While it does not explicitly list when not to use it, the guidance is clear enough for an agent to decide.

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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