---
title: "Eval and research"
description: "ralphy eval video for post-render QA and ralphy research for URL or topic teardowns."
---

Two verbs sit at the bookends of a project. `ralphy research` is the pre-production teardown — turn a URL, handle, or topic into a cited report a scenarist can act on. `ralphy eval` is the post-render QA — score a rendered mp4 across scene segmentation, audio, captions, and per-scene vision. Both are CLI-native entry points to skills (`/researcher`, `/evaluator`); the verbs are the machine contract.

## ralphy eval video &lt;path&gt;

Runs the full eval pipeline on a single mp4. Output: `eval-report.md` (human) + `eval.json` (machine).

```bash
ralphy eval video .ralphy/workspaces/<ws>/projects/demo-001/render/final.mp4
ralphy eval video ./some-other.mp4 --no-project    # standalone, no project context
ralphy eval video ./clip.mp4 --no-vision           # skip the per-scene LLM pass (cheaper)
ralphy eval video ./clip.mp4 --out-dir ./eval-out  # custom output dir
ralphy eval video ./clip.mp4 --vision-concurrency 5
```

The CLI summary returns `{ verdict, score, findings, severities, jsonPath, mdPath }`. The full report carries scene segmentation, loudness windows, dead-air spots, caption density, per-scene visual findings — sized for a downstream fixer agent to consume.

### What the pipeline does

1. ffprobe the input — duration, resolution, fps, codec.
2. Scene segmentation via ffmpeg scene-detect.
3. Audio analysis — EBU R128 loudness windows, dead-air windows.
4. Caption check — density per scene, gap windows.
5. Per-scene vision pass — frames extracted, sent through `cli/lib/providers/llm.ts`.
6. Score + verdict + findings written to `eval-report.md` and `eval.json`.

Per [AGENTS.md invariant #2](https://github.com/alecs5am/ralphy/blob/main/AGENTS.md), the vision pass routes through `cli/lib/providers/llm.ts` — agents never reach for raw provider SDKs.

### Quality gates

When the score crosses a refuse threshold, the verb raises one of `E_GATE_SCENARIO`, `E_GATE_IMAGE`, or `E_GATE_VIDEO` (see [Error catalog](/cli/error-catalog)). Two consecutive gate refusals on the same project are the agent's stop signal — report concrete options to the user rather than render again.

Full surface: [`/reference/cli/eval`](/reference/cli/eval).

## ralphy research

Topic-level research that aggregates multiple sources into one synthesis. Sibling to `ralphy ref <verb>` (single URL) — research composes refs into a cross-source report.

```bash
# Create a topic
ralphy research start italian-brainrot --question "How is the format evolving in 2026?"

# Add one or more sources
ralphy research add-source https://tiktok.com/@x/video/72939... --topic italian-brainrot
ralphy research add-source https://www.youtube.com/shorts/abc --topic italian-brainrot --frames 24

# Pull metadata only (no frames / transcript / vision)
ralphy research add-source https://twitter.com/x/status/123 --topic italian-brainrot --meta-only

# Synthesize the report (LLM)
ralphy research synthesize italian-brainrot
ralphy research synthesize italian-brainrot --model google/gemini-2.5-flash

# Inspect / list
ralphy research show italian-brainrot
ralphy research list
```

Output lands under `.ralphy/research/<topic>/`:

```text
.ralphy/research/italian-brainrot/
├── report.md          # final synthesis
├── sources.json       # every source + per-source analysis
└── state.json         # topic state (question, sources, last synth)
```

The `/researcher` skill is the human entry-point; this CLI is the contract underneath. Full surface: [`/reference/cli/research`](/reference/cli/research).

### Source pulls

`add-source` chains `ralphy ref pull` → `ref frames` → `ref analyze` → `ref blueprint` for each URL, then registers the result against the topic. `--meta-only` skips the heavy passes (useful for sources you only want to cite, not analyze deeply). `--frames <n>` caps the sample count.

### Synthesis

`synthesize` runs a cross-source LLM pass over every source's blueprint + transcript + analysis. Default model: `google/gemini-2.5-flash`. The report includes a cited findings section and per-source pull-quotes the agent can lift verbatim into a scenario.

## When to use which

| Symptom | Verb |
|---|---|
| User drops one URL, wants a teardown | `ralphy research add-source` (or the `/researcher` skill) |
| User wants a topic-wide audit ("what's trending in X") | `ralphy research start` + several `add-source` |
| User asks "is this video good?" | `ralphy eval video <path>` |
| Post-render gate before publish | `ralphy eval video <render>` |

## Related

- [Researcher playbook](https://github.com/alecs5am/ralphy/blob/main/docs/playbooks/researcher.md) — the agent-side workflow
- [Evaluator skill](https://github.com/alecs5am/ralphy/blob/main/.agents/skills/evaluator/SKILL.md) — eval triggers + invariants
- [Error catalog](/cli/error-catalog) — `E_GATE_*` codes
- [cli/commands/eval.ts](https://github.com/alecs5am/ralphy/blob/main/cli/commands/eval.ts), [cli/commands/research.ts](https://github.com/alecs5am/ralphy/blob/main/cli/commands/research.ts)
