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docker_events_summary

Aggregate Docker container lifecycle events (die, OOM, restart, kill, start) per instance over a lookback window to spot crash loops and restart patterns.

Instructions

Aggregate container lifecycle events (die/oom/restart/kill/start) on one instance over a lookback window. Read-only. Returns JSON: {events: [{container, event, count, last_at}]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_idYesInstance ID or name. '<account>/<name>' picks the server of one provider account; custom servers are 'custom/<name>'.
since_minutesNoLookback window in minutes (1-10080, default 1440).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.28.0
    • changedInput schema / properties / instance_id / description
      Previous value: -"Instance ID or name."New value: +"Instance ID or name. '<account>/<name>' picks the server of one provider account; custom servers are 'custom/<name>'."
  2. Addedv2.24.0
  3. Removedv2.23.8
  4. Addedv2.23.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully declares 'Read-only' and gives the exact return shape ({events: [{container, event, count, last_at}]}), which is real added value. However, it says nothing about permissions, cost/latency of aggregation, or whether counts are per-container or global, so the safety profile is disclosed but the operational behavior is thin.

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?

Three short sentences, front-loaded with the scope-constrained action, followed by the read-only flag and return schema. Every sentence contributes and nothing is padding.

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?

No output schema exists, but the description compensates by specifying the return JSON structure, and it flags read-only despite missing annotations. It is nearly complete for a simple two-parameter read tool; only the absence of instance-scoping caveats or event-filtering notes keeps it short of full.

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

Parameters3/5

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

Schema coverage is 100%, so both parameters (instance_id with account/name format, since_minutes with range and default) are fully documented in the schema. The description only echoes the lookback-window concept, adding no syntax or bounds beyond the schema, so baseline 3 is appropriate.

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?

States a specific verb (aggregate) plus a precisely scoped resource (container lifecycle events die/oom/restart/kill/start on one instance over a lookback window). The enumerated event types and 'one instance' scope clearly separate it from siblings like docker_logs, docker_log_summary, docker_stats, and docker_ps without needing to name them.

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?

Usage is only implied: 'over a lookback window' and 'on one instance' suggest the diagnostic scenario, but there is no explicit when-to-use-this-vs-docker_log_summary or docker_stats guidance, and no stated exclusions. An agent must infer the routing decision.

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