Renn F
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Build a complete user-facing documentation site (MkDocs Material) under docs/, served at roboco.dev/docs via a new gh-pages deploy workflow. - Sections: Get Started, The Company, the Tour, Operating the Panel, Choosing & Running Models, Cost & Observability, Optional Subsystems, Configure & Deploy, API Reference, Troubleshooting & Security (55 pages). - mkdocs.yml (Material theme; excludes the agent-facing rag/ corpus, internal scratch, and orphaned stub trees) and .github/workflows/docs.yml (mkdocs gh-deploy to gh-pages). - Retire the stale root usage.md and deployment.md to redirect stubs into the site. - Fix the docs tooling: add the pymarkdownlnt dependency + .pymarkdown.json, run serve-docs/lint-docs/fix-docs under the docs extra, add a build-docs strict gate. - Fix the roboco console-script entry point (cli, not the un-awaited async main). - README: correct the project-structure tree (optimal.py, alembic) and link the docs site.
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How agents are sandboxed
The most important thing to understand about trusting RoboCo with your repository: agents never touch your API, your database, or a shell directly. Every action an agent can take goes through a narrow, server-side gateway that only exposes the handful of verbs that agent's role is allowed to use. Capability is decided by role at spawn time — not by the model's good behavior.
Agents speak in verbs, not API calls
Each agent container talks to RoboCo through two thin MCP servers, both backed by a single server-side component (the Choreographer) that composes the real services behind the scenes:
| Server | What it exposes |
|---|---|
roboco-flow |
Intent verbs — the lifecycle actions: give_me_work, i_will_work_on, open_pr, i_am_done, claim_review, pass_review, complete, submit_up, submit_root, pr_pass, … |
roboco-do |
Content tools — commit, note, say, dm, evidence. |
Two more read-only servers give agents a read-only view of git (status, log, diff) and access to the knowledge base. That's the entire surface. There is no "run arbitrary SQL," no "call any endpoint," no general shell.
A role can only call its own verbs
At spawn, every agent is handed a manifest listing exactly the verbs its role may call — and nothing else. The manifest is built from a server-side role configuration and mounted read-only into the container. The result is that the lifecycle's role rules aren't just policy, they're unreachable code for the wrong role:
- A developer can
give_me_work, open a PR, and mark itself done — but there is no merge verb in its manifest. - QA can claim a review and pass or fail it — but it has no
commit. - A PR reviewer can pass or fail an assembled PR and post its review on the PR — but it never gets agent chat verbs.
- The Auditor is restricted to leaving a private note and reading evidence; it cannot
sayordm. It observes; it does not participate.
So when the lifecycle says "only QA can pass QA" or "only the CEO merges to master," that boundary is enforced at the gateway: the verb simply isn't available to anyone else.
Every action returns a structured envelope
Agents don't guess at state. Every verb returns a standardized envelope:
- On success:
{ status, task_id, next, evidence?, context_briefing }— wherenexttells the agent what to call next. - On error:
{ error, message, remediate, missing }— whereremediatetells the agent exactly how to fix it and retry.
That next / remediate contract is why agents move through the lifecycle reliably instead of flailing: the gateway leads them, step by step, and rejects anything out of order with an explanation rather than a crash.
The other guardrails
A few more protections run by construction, the same way on every backend (Claude or Grok):
- Claim-locking serializes work, so two agents can't grab the same task or race a merge.
- The token never enters the container. Your GitHub PAT is injected only for the moment of a git operation, orchestrator-side, and scrubbed from every clone — see Register a project.
- A prompt-injection guard screens task prompts, and a bash guard blocks credential-exfiltration and identity-forgery patterns.
- Rate limits and overloads park, they don't crash-loop. If a provider returns a 429 or a persistent overload, RoboCo queues that agent's work and probes for recovery instead of burning tokens retrying. You'll see an amber banner; the work resumes automatically when the provider does.
The practical upshot for you as operator: the workforce is structurally constrained to do its job and only its job. You're not relying on twenty-five models all choosing to behave — you're relying on the fact that the misbehaving action isn't on the menu.
Next
→ Watch it all in motion in the Tour, or head back to the lifecycle.