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system_events

Read-only

Stream real-time Docker events with filters, limit, and timeout to capture specific events or block until one arrives.

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
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that the call blocks until limit or timeout, that a quiet daemon would block indefinitely without timeout, and that SSH streams cannot be cancelled. It also explains memory (limit) and wall-clock (timeout) reasoning. This is rich behavioral context well 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.

Conciseness5/5

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

The description is well-structured with clear sections: intro, blocking conditions, SSH caveat, usage idiom, and args. Each sentence provides necessary information, and the 'wait for event' idiom paragraph justifies the tool's existence concisely. No fluff or repetition.

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?

For a tool with no output schema, the description covers return values (list of decoded event dicts, length <= limit), explains edge cases (idle stream, SSH), and gives practical usage guidance. It fully addresses the complexity of a streaming API, making it complete for an agent to invoke correctly.

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?

The 'args' section provides a one-line meaning for all 5 parameters, which is essential given the 0% schema description coverage. Limit and timeout are clearly defined with defaults. 'since' and 'until' are minimally described as timestamps, and 'filters' is vague, but the description compensates for the schema's complete lack of field documentation.

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 opens with 'Stream real-time events from the Docker server', using a specific verb and resource. It distinguishes itself from sibling system tools (system_info, system_ping) by focusing on event streaming and clearly states the bounded behavior (limit/timeout). The 'wait for next matching event' idiom further clarifies a unique use case.

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?

The description explicitly explains the core use case (waiting for a matching event) and even notes that 'there's no separate wait tool for this since the filtering this call already does covers it', thereby addressing alternatives. It also provides a caveat for ssh:// daemons, guiding when timeouts won't behave as expected, which is essential for correct usage.

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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