Tools provided
Tools the agent exposes — your AI client calls them automatically when it needs them.
- optimize_pipeline — Find where your CI pipeline spends its wall clock and propose the deterministic fixes: broken or missing dependency caches, steps that could run concurrently, oversized test jobs worth sharding, and redundant steps.
- forecast_pipeline_health — Read your CI run history and say where the pipeline is going: the per-stage trend fitted by least squares, the stage that will bottleneck first, and whether the growth is work time or queue time.
- plan_deployment — Turn a change, a set of environments and your own deployment record into a staged rollout: the order, the gate on each stage and why, the signals to watch, the stop conditions, and the soak time. It plans only.
- plan_rollback — Work out how to undo a deployment and where undoing it stops being possible: the point of no return, the steps in reverse order, and the data-recovery notes. It plans only.
- generate_runbook — Turn an incident or operational-task description into a structured runbook: diagnosis, mitigation, verification, rollback and communication — or validate and lint a draft runbook you already have.
- run_full — Run every capability you supplied the input for, in registry order, and return one report. Capabilities whose input is missing are listed as skipped.
- list_capabilities — List what this agent can do: every tool it advertises, what each one is for, and the arguments each one reads.
- plan_inputs — Plan the inputs for a tool: returns the questions to ask, the JSON schema of the arguments, and a ready-to-edit example.
- discover_intent — Understand your goal and co-design the exact input through clarifying questions before anything runs.
- open_form — Opens an interactive form that collects the run arguments. The form is the entry point for running the agent.
- run_form — Internal: invoked by the open_form form when the user submits. Not for direct use.
