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This walks through all three layers of Console in one pass: connect your data, use an agent interactively, then automate it as a workflow. Budget about twenty minutes.

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1. Connect a repository

Sign in to the web console and open Connections. Install the Console GitHub App for your organization, granting access to at least one repository you’re comfortable experimenting on. The repositories you grant appear under Projects — the code agents can read.
Pick a real repository rather than an empty one. Agents reason about actual code, so a repository with real application logic gives you a far better sense of what Console does.

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2. Ask an agent something

Open Console in the sidebar and start a new chat. Ask a question about the repository you just connected:
Look at this repository and tell me where user input reaches a database query without parameterization.
Watch what happens. The agent clones the repository, reads files, searches, and traces call paths — and you see each tool call as it runs. It decides what to look at next based on what it just found. Try following up. Is that actually reachable from an HTTP handler? The agent goes back to the code to answer. If it confirms something, it records a finding — durable, with its reasoning attached.

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3. Write an agent

The built-in library covers a lot, but Console is most useful when the agents are yours. Open Agents and create one:
Save it. That’s a working agent — YAML frontmatter declaring its name, model, and tools, plus instructions as the body. See writing an agent for every field.

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4. Automate it

Open Workflows and click New workflow. Click Save. Console’s orchestrator reads the description as the goal and briefs your agent against it, so write it as an instruction. See create a workflow.

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5. Run it

Click Run workflow, select your repository, and leave the git ref empty to use the default branch. Console provisions a sandbox, clones the repository, and runs your agent. Click View runs to watch the chain: each step shows status and duration as it completes, and the run page lists findings and output deliveries when it’s done. Your pull request trigger is live too — open a pull request in that repository and the workflow fires on its own, against the pull request’s head.
The Comment on triggering pull request output only acts on pull-request runs, so it’s skipped on the manual run you just did. Open a pull request to see it deliver.

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What you just built

  • Data — a connected repository agents can read
  • An agent — your own, defined in YAML frontmatter and Markdown
  • Workflow — that agent running automatically on every pull request, reporting to your team
Each layer is replaceable independently. Swap the agent, add a step, change where results go — the rest keeps working.

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Where to go next

Agents & detections

Skills, detections, and the full tool surface.

Triage an existing backlog

Connect a scanner and find what’s actually reachable.

Gate merges on review

Block merging until security review passes.

Install the CLI

Run the same agents on local, uncommitted code.