Agent Pipelines
Build your own small AI review agents — and run the community's.
Agent Pipelines let you build your own small AI review agents and run them on any pull request. Each agent is a short prompt plus an allowlist of the context it may read — the diff, the PR details, linked tickets, specific files, or recent commit history. Agents are advisory only: they see just the context you grant them, and they can never post, approve, merge, or otherwise change the pull request.
Everything lives under Settings → Agent Pipelines.
PR Flow's AI is one switch
Turning Agent Pipelines on enables PR Flow's AI. All of PR Flow's built-in helpers — deep review, PR complexity and risk, review-thread summaries, the review-summary draft, and the discuss assistant — appear right in your Agent Pipelines list, badged Default. Switch each one on or off individually, and tailor any of their prompts to your team's voice (a one-click Reset restores the original). However you rewrite a built-in helper's prompt, its results stay dependable — the required output format is always applied.
Upgrading from an older version carries your setup forward untouched: whatever you had on stays on, anything you'd turned off stays off, and an active license turns the whole set on for you.
You choose which AI provider runs your agents — a CLI, a local model, or a company gateway. See AI Features for provider setup and per-task routing.
Building an agent
Create an agent with a simple form, or by pasting or importing YAML. An agent has:
- A prompt — the instructions the agent follows.
- Context — the allowlist of what it may read (see below).
- An output type — either inline findings (severity-tagged notes pinned to specific lines, which you can dismiss or turn into review comments) or a freeform note you can copy.
- A trigger — the moment it runs.
You can export any agent you build to a file to share it.
Context is the privacy boundary
Context selectors are the only way information reaches the model — the prompt can never ask for more than you granted. Each selector maps to one thing:
| Selector | What the agent sees |
|---|---|
| Diff | The pull request's code diff |
| PR details | Title, description, changed files, and open review threads |
| Linked ticket | Tickets referenced by the PR (e.g. a Jira issue) |
| A specific file | One file at the PR's latest commit |
| Commit history | Recent commit subjects and authors on the changed files |
Agents run with no ability to read your wider filesystem, run commands, or reach the network. Because a shared agent's prompt might come from someone else, this matters: the input arrives pre-resolved through the selectors you approved, and the output is either validated findings or plain text — there's nothing for a malicious prompt to hijack.
When agents run
An agent's trigger is the moment it fires:
- When the PR appears on your board — great for board-wide pre-evaluation; runs once per pull request.
- When you push a draft of your own PR — a first look before anyone else sees it.
- When one of your PRs starts conflicting — a heads-up the moment it happens.
- When you open the review — its notes are ready as you start reading.
- When you open the review submit sheet — ready as you write your summary.
- On demand — from the Agents panel, the review's AI menu, or a keyboard shortcut.
Automatic runs are yours to govern. One master Automatic triggers switch pauses every self-starting run — custom and built-in alike. You also choose how many agents run at once and set an hourly per-repository safety cap. On-demand runs and the ones tied to actions you took (opening a review, pressing a button) are never held back.
If an automatic agent fails repeatedly, PR Flow pauses further automatic attempts on an escalating schedule — first for minutes, then longer if failures continue. The agent row shows when it will try again, while on-demand runs stay available for testing or recovery. Any successful run clears the pause.
A note on honesty: a true "before you publish" moment isn't something PR Flow can observe from the outside, so "when you push a draft" means as the draft is pushed.
Running agents
Open a pull request's Agents panel to run any agent on demand. Findings arrive pinned to the lines they flag; notes gather in their own panel beside the diff. In the in-app review, findings show as inline pins tagged with the agent that raised them. A Prep AI action runs your review agents ahead of time, so results are already waiting when you open the review.
The Community Store
Discover and install agents others have shared from the Community Store tab — or browse the full catalog on the web in the Agent Gallery.
Every install shows you the agent's exact prompt and the precise context it's allowed to read before anything is saved. If a shared agent you use is later updated, the version you approved keeps running until you review and approve the change. Edit an installed agent and it's clearly marked Edited, so you always know it differs from what you approved. You can also install an agent straight from the web with a one-click link — it only ever opens the approval screen, never installs silently.
If an approved install overlaps an active agent in the same trigger and output slot, PR Flow keeps the new agent switched off and explains the conflict instead of silently replacing your current setup. You can jump straight to the Agent Library to choose which agent should occupy that slot.
Share your own. The store is an open, community-run catalog on GitHub. Publish an agent by opening a pull request against the community agents repo — its contribution guide walks through the agent format and how entries are reviewed.
Profiles
Group your agents into profiles — named, switchable sets — and flip which set runs in a single click. Keep one lineup for reviewing and another for architecture work.
Keeping agents useful
PR Flow keeps a metadata-only record you can inspect and export:
- Settings → Logs → Agent runs — every run, with which agent ran, what triggered it, how long it took, and the outcome. Prompts and results are never stored there. Export the whole log to JSON for your own audit.
- Dismiss-rate hint — if most of an agent's findings end up dismissed, its row shows a gentle nudge to tighten the prompt. This is measured entirely on your own device — PR Flow sends nothing home.
For teams
An administrator can push a shared profile of agents to everyone, with required agents that always stay on, and can lock any built-in AI helper on or off across the team. Managed agents and profiles remain read-only on each seat, so a local agent can't overwrite an organization-owned identifier. As with all of PR Flow's AI, prompts and code go only to the provider you choose — reach out for Enterprise setup.