Build your own Octopus dashboards with llms.txt and an AI coding agent

Octopus Deploy’s llms.txt feature provides a consolidated Markdown reference for its REST API, enabling AI coding agents to understand authentication, space scoping, endpoints, request types, deployment-step properties, and supported action settings without navigating extensive documentation. Using Claude Code with a local Octopus instance, the author demonstrated how an agent used this file to create realistic multi-tenant test data for a fictional retailer platform, including projects, deployment processes, releases, targets, variables, runbooks, and teams. The agent then built custom dashboards such as a tenant rollout board that identifies releases behind schedule, missing variables, and pending approvals, and a team health board that prioritizes failures and approval bottlenecks while showing deployment, target, and freeze status. It also produced a Sankey-style release-flow visualization connecting releases, environments, and tenants to reveal deployment patterns and anomalies. The post recommends starting with read-only API tasks, validating results in the Octopus portal, using API errors to refine requests, and protecting credentials by keeping API keys server-side behind a proxy rather than exposing them in browser-based dashboards.

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