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Glama

get_deployments

Retrieve deployment history for a container, or a detailed view of one deployment with status, error code, and build-log tail to diagnose failures.

Instructions

Deployment history of a container, or one deployment in detail (status, error code/message and build-log tail — use this to diagnose a failed build).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoList size, default 10
containerNoContainer name or id (for the list)
deployment_idNoOne deployment in detail

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does it well by disclosing the returned information for the detail view: status, error code/message, and build-log tail. The wording 'history' and 'detail' implies a read-only diagnostic operation; it does not mention pagination or no-parameter behavior, but no mutation or unexpected side effects are hidden.

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?

One compact sentence that front-loads the resource and modes before the parenthetical diagnostic detail. There is no filler or redundant restating of the tool name.

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

Completeness3/5

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

The description covers the two main call modes and the diagnostic use case, which is the core context needed. It leaves some ambiguity around required/absent identifiers (container and deployment_id are both optional in the schema) and does not describe the fields returned in the list view, and there is no output schema to fill that gap.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning by explicitly associating container with the historical list and deployment_id with the detailed diagnostic output. It also names the fields an agent can expect when using deployment_id, which the schema does not.

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 identifies deployments as the resource and distinguishes a list-style history from a single-deployment detail view, including concrete output fields (status, error code/message, build-log tail). It does not explicitly name a sibling tool, but the diagnostic use case makes the purpose distinct from get_logs/get_status.

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?

It gives a concrete trigger—'use this to diagnose a failed build'—which tells the agent when the detail view is relevant. It does not provide explicit when-not-to-use or alternative tool names, but the context is clear enough to select this tool.

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