> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/getcompanion-ai/feynman/llms.txt
> Use this file to discover all available pages before exploring further.

# Peer Review

> Simulate an AI research peer review with likely objections, severity grading, and a concrete revision plan.

The peer review workflow simulates a thorough academic peer review of a paper, draft, or research artifact. It produces severity-graded feedback covering methodology, claims, writing quality, and reproducibility — using the same `reviewer` subagent that verifies outputs in other Feynman workflows.

## Invocation

<Tabs>
  <Tab title="CLI">
    ```bash theme={null}
    feynman review "<artifact>"
    ```
  </Tab>

  <Tab title="REPL">
    ```
    /review <artifact>
    ```
  </Tab>
</Tabs>

**Examples**

```bash theme={null}
feynman review "arxiv:2401.12345"
feynman review my-draft.md
```

```
/review arxiv:2310.06825
/review ~/papers/my-draft.pdf
```

You can pass an arXiv ID, a URL, or a local file path.

## Workflow stages

<Steps>
  <Step title="Plan">
    Before starting, the lead agent outlines what will be reviewed, the review criteria (novelty, empirical rigor, baselines, reproducibility, and so on), and any verification-specific checks needed for claims, figures, and reported metrics. The plan is presented to you for confirmation before proceeding.
  </Step>

  <Step title="Gather evidence">
    For papers or artifacts with associated code and cited work, the `researcher` subagent gathers evidence: it inspects the paper, the codebase, cited sources, and any linked experimental artifacts, saving findings to `<slug>-research.md`.

    <Note>
      For small or simple artifacts where evidence gathering is overkill, the `reviewer` subagent is run directly without a prior research pass.
    </Note>
  </Step>

  <Step title="Review">
    The `reviewer` subagent reads the document end-to-end against standard academic criteria:

    * Are the claims supported by the methodology?
    * Does the experimental design have potential confounds?
    * Are baselines appropriate and fairly compared?
    * Is the paper reproducible from the description given?
    * Are reported metrics consistent with the experimental setup?

    The reviewer uses `<slug>-research.md` as source material for inline annotations.
  </Step>

  <Step title="Severity grading">
    Each piece of feedback is assigned one of three severity levels:

    | Severity  | Meaning                                                          |
    | --------- | ---------------------------------------------------------------- |
    | **FATAL** | Fundamental issues that undermine the paper's core validity      |
    | **MAJOR** | Significant problems that should be addressed before publication |
    | **MINOR** | Suggestions for improvement that do not block acceptance         |

    If the first review finds FATAL issues and they are fixed, one additional verification-style review pass is run before delivery.
  </Step>

  <Step title="Deliver">
    Exactly one review artifact is saved to `outputs/<slug>-review.md`. The report ends with a `Sources` section containing direct URLs for every inspected external source.
  </Step>
</Steps>

## Outputs

| Artifact                          | Path                       |
| --------------------------------- | -------------------------- |
| Research evidence (when gathered) | `<slug>-research.md`       |
| Peer review report                | `outputs/<slug>-review.md` |

## Review report structure

* **Summary assessment** — overall evaluation and recommendation
* **Strengths** — what the paper does well
* **FATAL issues** — fundamental problems that must be addressed
* **MAJOR issues** — significant concerns with suggested fixes
* **MINOR issues** — smaller improvements and suggestions
* **Inline annotations** — specific comments tied to sections or claims in the document

## Subagents used

| Subagent     | Role                                                      |
| ------------ | --------------------------------------------------------- |
| `researcher` | Gathers evidence from the paper, code, and cited work     |
| `reviewer`   | Produces the peer review with severity-graded annotations |

## Customization

You can focus the review by being specific in your prompt:

```
/review arxiv:2401.12345 focus on the statistical methodology in Section 4
/review my-draft.md check the claims in the experiments section against the reported numbers
```

The reviewer adapts its analysis to your priorities while still performing a baseline check of the full document.

## Related

* [Paper Audit](/workflows/audit) — compare paper claims against a public codebase
* [Experiment Replication](/workflows/replication) — execute replication steps to verify experimental claims
* [Deep Research](/workflows/deep-research) — investigate the broader context before reviewing