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Nav: Agents | URL: /agents An agent is an autonomous worker installed on one repo. It does a job on a schedule, reports evidence for everything it does, and holds the calls a human should make for your Inbox. Outrider — a GitHub Action that turns recent research into draft PRs — is the first flagship agent; more agents with other functions are coming. The Agents view is the fleet index — every repo you’ve installed on, its state, and its last outcome — with + Set up an agent to add another. Click any agent to open its report.

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Set up an agent

Click + Set up an agent. The setup wizard is the in-app twin of remyxai outrider init:
The Set up an agent wizard: repository picker with the Remyx GitHub App confirmed installed, the research-interest dropdown on 'Create one from this repo automatically', Review vs Auto mode radios, LLM backend radios showing Anthropic (Claude), Z.ai (GLM), and Moonshot AI (Kimi) all connected, and the Advanced models-per-phase fold with Two-tier selected — a Z.ai glm-5.2 drafter and an Anthropic claude-opus-4-8 refiner
1

Repository

Pick from your GitHub repos or paste a URL. The wizard preflights the Remyx GitHub App on that repo — the App is how agents author PRs and Issues as remyx[bot] (without it they’d come from github-actions[bot]). If it’s missing, the wizard shows the one-click install link and unlocks automatically once GitHub records it.
2

Research interest driving the agent

Create one from this repo automatically (the default — Remyx derives the interest from the repo’s code and history) or pick an existing active interest.
3

Mode

  • Review — the setup PR and every draft wait for you.
  • Auto — the setup PR merges itself; drafts still wait for you.
4

LLM backend

Anthropic (Claude), Z.ai (GLM), or Moonshot AI (Kimi) — the wizard preselects a connected provider and flags one that isn’t connected yet. Under Advanced — models per phase you can choose the two-tier drafter/refiner layout.
Provisioning issues the repo a scoped agent key (rmxa_), writes the workflow file, and opens a bot-authored setup PR — merge it (or let Auto mode merge it) to activate the agent.
From the terminal

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Provisioning states

Each agent row shows its status chip, inline Run now / Pause actions, and its last outcome:
Agent rows in the fleet index: each repo with its status chip (active, or setup PR open linking to the PR), Run now and Pause actions, and the last outcome — a discussion, a skip with its reason, or 'Provisioned · awaiting first run'
The chip is derived the same way the CLI’s preflights reason about it:

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Run now / Pause

  • Run now dispatches a one-shot run outside the schedule. Available once the setup PR is merged and the agent isn’t paused.
  • Pause revokes the agent’s key: the next run fails auth immediately. The workflow file stays in the repo; nothing else is touched. Resuming is a fresh re-provisioning (new key, new setup PR). Pausing here, revoking the agent key under Account, and the MCP pause_agent tool all do the same thing.
From the terminal

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The agent report

Click an agent to open its report at /agents/<repo>. It leads with a KPI strip and Findings — each finding deep-links into the evidence it came from — over a shared date window (default last 7 days, presets up to All time) that rides the URL, so any view is shareable. Two header buttons: Ask about this agent and Configure. Anything blocking the agent is a banner up front; healthy agents get Run now.
One agent's report: KPI strip (27 dispatches, 1 draft opened, 2 leads awaiting a call, $17.04 spend at $5.68 per artifact), findings such as '7 runs failed before reporting' and ''already tried / duplicate' dominates demotions' — each with an evidence link — and the Evidence list of Runs, Direction, and Activity trace sections

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Runs

Every run the agent has reported, in weekly rollups, filterable by outcome and searchable by title, arXiv id, or status: Each row shows the artifacts, the run’s cost, and an Analyze › action that pulls the run’s job log and returns a root-cause read with a suggested next step.

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Direction

What the agent has learned from your decisions. Every merge, skip, and discussion re-weights what it proposes next: Each direction is evidence-backed — expand it to see the specific PRs, Issues, and runs it was learned from.

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Activity trace

The agent’s event stream, grouped by week: Merged, Closed, Drafts, Discussed, Failed runs, Skipped — each event linked to its artifact, with skip reasons attached.

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Configuration

The agent’s operating setup, editable in place: repository, interest, workflow file, setup PR, model backend (changing it re-provisions with a fresh setup PR), and status with Pause / Resume. The Signal panel lists what feeds this agent’s decisions: GitHub merge history (the ranking baseline), the repo’s research brief, validation runs, Linear tickets (interfaces under active work route risky candidates to discussion), and — when connected — A/B ship-rate feedback.

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Ask about this agent

A chat drawer grounded in the agent’s real data — runs, telemetry, failing-run log tails, open artifacts, direction — via read-only tools. It explains; actions like triggering or pausing stay behind the app’s confirm-gated buttons. Inbox Ask links land in this same drawer, focused on the relevant run.

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Where agents surface elsewhere

  • The fleet rolls up in Reports; items needing you land in the Inbox.
  • An agent can belong to several Projects — link it under the project’s Agents section.
  • The full fleet is scriptable via the MCP tool plane and the REST API.

Actions

What actually runs in the repo’s GitHub Actions

Model backends

Anthropic / Z.ai / Moonshot, and the two-tier pattern

Inbox

Where an agent’s drafts and held calls wait for you

Reports

The fleet in one view