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openl-tablets

OpenL MCP Server

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List Active Deployments

openl_list_deployments
Read-onlyIdempotent

List active production deployments with optional filters for repository and project, returning deployment names, repositories, and revisions.

Instructions

List active deployments across production environments, optionally filtered by production repository ID and deployed project name. Returns deployment names, repositories, and deployed project revisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
projectNoDeployed project name to filter deployments by.
repositoryNoProduction repository ID to filter deployments by.
response_formatNoResponse format: 'json' for structured, round-trippable data (default), 'markdown' for human-readable output, 'markdown_concise' for a brief summary (1-2 paragraphs), or 'markdown_detailed' for full details with contextjson

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changedv1.2.0
    • addedInput schema / properties / project
      Added value: +{
      +  "description": "Deployed project name to filter deployments by.",
      +  "type": "string"
      +}
    • addedInput schema / properties / repository
      Added value: +{
      +  "description": "Production repository ID to filter deployments by.",
      +  "type": "string"
      +}
    • changedInput schema / properties / response_format / default
      Previous value: -"markdown"New value: +"json"
    • changedInput schema / properties / response_format / description
      Previous value: -"Response format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with context"New value: +"Response format: 'json' for structured, round-trippable data (default), 'markdown' for human-readable output, 'markdown_concise' for a brief summary (1-2 paragraphs), or 'markdown_detailed' for full details with context"
  2. First observedv0.0.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is established. The description adds useful behavioral context by specifying the 'active' state, 'production environments' scope, and the returned fields, which goes beyond what the annotations alone provide.

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 a single, front-loaded sentence that states the action, scope, optional filters, and return contents without any filler. Every clause adds information, and no space is wasted on redundant phrasing.

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?

For a read-only list tool with five optional parameters and no required inputs, the description covers the main operational need: what it lists, how it can be filtered, and what the result contains. It does not mention ordering or pagination explicitly, but the schema documents limit/offset defaults and the annotations cover safety, making the description adequate.

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?

The schema describes project, repository, and response_format, but leaves limit and offset without semantic descriptions. The tool description adds clarity by calling repository a 'production repository ID' and project a 'deployed project name,' but it does not compensate for the missing pagination semantics beyond what the schema already supplies.

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 uses a specific verb and resource ('List active deployments'), defines the scope ('across production environments'), and names the two optional filters. It also states what is returned ('deployment names, repositories, and deployed project revisions'), which clearly separates it from sibling tools like openl_list_repositories or openl_list_deploy_repositories.

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 gives clear context for when to use the tool: when the agent needs active production deployments, optionally filtered by repository or project. It does not explicitly exclude alternatives or name sibling tools for comparison, but the scope and optional filters make the intended use obvious.

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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