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container_wait

Read-only

Block until a Docker container reaches a specified condition—stopped, healthy, or a log pattern—and report whether it was met or timed out.

Instructions

Block until a container reaches a condition: stopped, "healthy", or its logs contain a pattern.

One contract for every mode: never raises on timeout — the result always carries met (condition reached) and timed_out. The stop conditions ("not-running"/"next-exit"/"removed") use the daemon's blocking wait and fill status_code/error (the container's exit info); "healthy" polls the container's HEALTHCHECK every poll_intervals and fills health/status; "log-match" polls recent logs every poll_intervals for pattern and fills matched_line. For a compose project use compose_wait; for swarm services use service_wait.

Health semantics: with no HEALTHCHECK defined, once the container is running the tool returns promptly with health: null and met: false (false = "not confirmed healthy", not "unhealthy" — check health to tell them apart). A container that exits before becoming healthy returns its terminal status and met: false.

Log-match semantics: pattern is matched as a plain substring by default — safe against any input, including adversarial ones. Pass regex=True to match pattern as a regular expression (via re.search) instead; only do this with patterns you trust, since a regex with catastrophic backtracking run against attacker-influenced log content can exhaust CPU (ReDoS). Checks stdout and stderr, most recent lines first within each poll. If the container exits/dies before the pattern ever appears, returns promptly with met=false (not timed_out) — no further logs can arrive, so there's nothing to keep polling for.

args: id_or_name - The container id or name until - Condition to wait for: "not-running" (default), "next-exit", "removed", "healthy", or "log-match" (requires pattern) timeout_seconds - Max seconds to wait before returning with timed_out=true (default 600) poll_interval - "healthy"/"log-match" only: seconds between re-checks (default 2, > 0); capped by the time left so a large value can't push the total wait past the timeout pattern - "log-match" only: substring (or, with regex=True, a regular expression) to look for in the container's logs regex - "log-match" only: treat pattern as a regular expression instead of a plain substring returns: dict - {"container", "until", "met", "timed_out", "status_code", "error", "health", "status", "matched_line", "waited_seconds"}; stop modes fill status_code/error, "healthy" fills health ("starting"/"healthy"/"unhealthy", or null with no healthcheck) and status, "log-match" fills matched_line when met and status if the container exited without matching.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regexNo
untilNonot-running
patternNo
id_or_nameYes
poll_intervalNo
timeout_secondsNo
Behavior5/5

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

Beyond the readOnly/destructive annotations, the description discloses non-obvious behaviors: never raises on timeout, always returns `met` and `timed_out`, different condition modes fill different result fields, health semantics when no HEALTHCHECK exists, and log-match substring/regex behavior including a ReDoS warning. This is rich, context-adding transparency with no contradiction.

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?

Though lengthy, the description is efficiently organized into clear sections: the core purpose, a shared contract, mode-specific details, health and log-match semantics, and an args/returns reference. Every section earns its place and is front-loaded with the most critical information.

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?

The description is exceptionally complete for a complex multi-mode tool with no output schema. It explains the return dict, which fields each mode populates, how edge cases resolve (e.g., exit before health, exit before log match), and how poll_interval caps against timeout. No significant context is missing.

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 no descriptions, but the description's args section thoroughly explains each parameter: id_or_name, the until enum with defaults, timeout_seconds, poll_interval with capping behavior, pattern semantics, and regex. This adds full meaning beyond the bare 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 opens with a clear, specific verb and resource: 'Block until a container reaches a condition: stopped, "healthy", or its logs contain a pattern.' It enumerates the distinct condition modes and explicitly distinguishes from siblings by pointing to compose_wait for compose projects and service_wait for swarm services.

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 provides explicit guidance on when to use this tool versus alternatives: 'For a compose project use compose_wait; for swarm services use service_wait.' It also gives mode-specific behavior, timeout semantics, and edge cases, making appropriate usage clear.

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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