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events

Read-only

Stream real-time Docker events, returning a list of events capped by count or timeout to prevent indefinite waiting.

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).

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 annotations (readOnlyHint, destructiveHint), the description discloses critical behavioral traits: the streaming nature, bounding conditions, potential indefinite blocking without timeout, and the SSH daemon limitation. This adds significant value beyond what annotations provide.

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, beginning with the main purpose followed by detailed behavior and parameter explanations. It is concise enough to read quickly while containing essential details. A minor improvement could be trimming some redundancy, but overall it is effective.

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

Completeness4/5

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

Given the moderate complexity (5 parameters, no output schema, nested object), the description covers the main behavioral aspects and parameter semantics well. It includes a return type but lacks explicit detail on filter format or event dict structure. Still, it is sufficiently complete for an agent to use the tool 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?

With schema description coverage at 0%, the description fully compensates by explaining each parameter's purpose and interaction (since, until, filters, limit, timeout_seconds) and the return value. It clarifies the bounding logic and default values, providing meaning beyond the schema.

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 it streams real-time events bound by limit or timeout. It uses specific verbs ('stream', 'bounded by') and specifies the resource ('real-time events from the Docker server'). While it does not explicitly differentiate from sibling tools, the purpose is distinct and unambiguous.

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 (streaming events) and includes important caveats about SSH daemons and potential indefinite blocking. It explains the bounded behavior and the trade-offs between limit and timeout, but does not mention alternative tools or when not to use.

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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