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system_events

Read-only

Stream real-time Docker server events with configurable limits and timeout to avoid indefinite blocking.

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 annotations (readOnlyHint=true), the description explains streaming behavior, memory capping, blocking, and the SSH limitation. It also clarifies return conditions and the watchdog mechanism, providing full transparency.

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, front-loaded purpose, and every sentence adds value. It is concise yet comprehensive, covering all necessary details without redundancy.

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 the complexity (5 params, no output schema, nested objects), the description is complete. It explains all parameters, return type, and provides usage idioms and caveats, leaving no gaps for the agent.

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?

With 0% schema description coverage, the description compensates fully by explaining each of the 5 parameters (`since`, `until`, `filters`, `limit`, `timeout_seconds`) in detail, including their purpose and default values.

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 Docker events, bounded by `limit` or `timeout_seconds`. It distinguishes from sibling tools like `system_info` or `container_logs` by specifying the event-streaming nature and the behavior of returning when conditions are met.

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 describes when to use (e.g., 'Wait for the next matching event' idiom) and when not to (SSH caveat). It also mentions that there is no separate wait tool, providing clear guidance on alternatives and limitations.

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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