git:20260907.8226e4d to git:20260908.8620bd3

---

name: kinocut

description: Use Kinocut for guarded video editing, source-backed planning, FFmpeg operations, media analysis, subtitles, audio workflows, Hyperframes or Revideo rendering, repurposing packages, and release checkpoints through an MCP server, Python client, or CLI. Trigger when an agent needs to inspect, plan, edit, render, validate, or package local media safely.

---

# Kinocut

Use Kinocut when an agent needs a structured video-editing surface instead of hand-writing FFmpeg commands. It exposes MCP tools, a Python client, and a CLI for editing, analysis, subtitles, audio, Hyperframes, layered compositing, and local repurposing workflows.

## Default path (do this first)

1. `kino doctor` then `kino --format json info <file>`.

2. Plan with `video_intent` (optional `goal=` compiles a cutfile; a 360/desk/table/`x4` goal also proposes a `360_assembly_plan`) — do not list 200 tools.

3. Render (`video_cutfile_render`, `video_edit`, workflow, or a single engine tool). For 360: `video_review_decide` approve/reject on that plan, then render — never render a `proposed` plan. `.insv` is rejected; need a stitched 360 MP4. Guide: `docs/360_ASSEMBLY.md`.

4. `video-quality-check` / `assert_quality`. Sync `repurpose` and `shorts-package` fail-closed at score 80 unless skipped/`allow_fail`.

5. Human visual/audio review. Never treat a receipt as published.

Depth (rescue, salvage, composite, Hyperframes, thin sound S12): `docs/TOOLS.md`, `docs/RESCUE.md`, `docs/WORKFLOWS.md`. Workflow allowlist: probe, trim, resize, convert, crop, add_text, merge, composite_layers, burn_in.

## Revideo local code-video flow (development tip)

Use `revideo_materialize`, `revideo_install`, and `revideo_render` when the

caller needs an inspectable staged project. Use `revideo_render_job` for the

same guarded steps in one call. A supplied scene is trusted executable

TypeScript: inspect it before use and never run untrusted scene code. Dependency

installation may access npm; rendering runs locally against Kinocut's pinned

template. The render receipt binds observed media and output bytes to the exact

bounded on-disk job-file digest. `.mp4`, `.webm`, and `.mov` select pinned MP4,

WebM, and ProRes 4444 exporter modes and are verified before publication. Verify the receipt against the output bytes, run `video_quality_check`

and `video_release_checkpoint`, then require human visual review.

## Start Here

- Read `../../README.md` for install and the safety contract.

- Run `kino doctor` before FFmpeg / Hyperframes / AI extras.

## Choose A Surface

- MCP: best for Claude Code, Cursor, Codex-style clients, and other agent hosts. Configure `uvx --from kinocut kino`.

- CLI: best for direct local edits, quick diagnostics, `composite-layers --dry-run`, batch jobs, and CI-friendly JSON output.

- Python client: best for repeatable pipelines that need structured results, output paths, and saved layer-plan receipts.

## 360 dual-cam assembly (published 1.14.0)

Use when the source is a **stitched equirect 360 MP4** from any camera (Insta360, Ricoh Theta, GoPro MAX, DJI Osmo 360, …) and the ask is two virtual cameras as split / switch / PiP / single.

1. `video_intent(verb="reformat_vertical", goal="desk 360 split 9:16", source=ABS_PATH)` or `Client.propose_360_assembly(...)`.

2. Show cameras, layout, and storyboard stills. Do not invent yaw/pitch.

3. `video_review_decide` / `Client.decide_360_assembly` with `approve` or `reject`.

4. Render only an approved plan (`Client.render_360_assembly` or `video_review_decide` + `output_path`).

There is no `video_360_*` MCP tool and no `kino 360` command. CLI `intent` and `review-decide` do not run this compiler. Director plugs (Ollama first; cloud only with `allow_cloud`) may propose JSON; they never write pixels. In pip 1.14.0.

## Product / object matte (published in 1.15.1)

The optional object-matte extra is available in published 1.15.1. Use the **existing** `hyperframes-remove-background` / `hyperframes_remove_background` command. Default model is people. For catalog SKUs, jewelry, bottles, shoes, packaging, or anything that is not a person:

1. `hyperframes_remove_background(info=true)` — lists models, no download.

2. `pip install "kinocut[object-matte]"` then `model="birefnet-general"`.

3. Optional `--mask-interval 3` on product video. Optional equipment overlay for leftover turntable/stand/tripod/sweep.

4. Composite onto a shop plate with `composite-layers`. Keep every `src` inside the spec directory.

Do **not** invent `video_product_matte` or a 197th tool. Do **not** fall back to the people model when the object extra is missing. Guide: `docs/PRODUCT_MATTE.md`. Example: `examples/product-matte/`.

## Dedicated Video Rescue

Use `video_rescue_*`, `rescue-*`, or `Client.rescue_*` when the request is to fix one local

clip while preserving its source, story, and timeline.

Required sequence:

1. Call plan and save the plan artifact.

2. Present `safe_repairs`, `recommendations`, `unavailable_repairs`, `blocked_repairs`,

previews, package intents, capabilities, and estimate to the user.

3. Inspect the plan before render. Obtain or infer explicit approval only for IDs in

`safe_repairs`; omitting the ID list means all safe IDs in the reviewed plan.

4. Call render with exactly those approved safe IDs.

5. Inspect the render receipt, then report package paths, unavailable sidecars, integrity,

gating verification, privacy, resume, and cleanup state.

Never render directly from an unreviewed plan. Never add recommendation IDs, unavailable

IDs, or blocked IDs to approval. Never use cloud tools, burn rescue captions, rewrite the

source, or treat `unavailable` as automatic failure. A cancellation or verification failure

must remain unpromoted or quarantined.

## Deterministic AI-video Inspection

Use `video_ingest`, `video_preflight`, and `video_inspect_temporal` (or their flat CLI and

Python equivalents) when generated footage needs evidence before an edit decision. Ingest

first, then address the asset by its returned hash. Never replace that asset id with a host

path or construct an `AssetRecord` at the public boundary. Temporal inspection returns the

full sampled-frame and motion-strip package, deterministic findings, and explicit unavailable

provider capabilities. Provider absence is expected and must not trigger a download or a

network fallback.

## Governed AI-video Review and Salvage

Use `video_verdict`, `video_acceptance_eval`, `video_body_swap`, and `video_salvage` (or

their flat CLI and Python equivalents) for exact-asset editorial decisions and derivative

recovery. A non-approved verdict may capture agent analysis, but an approved disposition

must bind an active, exact human decision with explicit requirement, role, and artifact

evidence. Acceptance evaluation is derived rather than an approval action, and every

salvage output starts in a fresh non-approved review slot.

Never invent a decision id, pass an unstored approval, or look for a force/override route.

Body swap rejects duration mismatch unless the caller chooses an explicit policy. Salvage

requires an existing private project, a stored source asset, a bounded recipe policy, and

an exact acceptance-spec id.

Acceptance evaluation takes active stored `acceptance_spec_id` and `verdict_ids`, never

caller-built evidence objects. Public body swap always takes `project_dir` first and both

source paths must resolve to active assets in that exact project.

Read `docs/AI_VIDEO_REVIEW_AND_SALVAGE.md` before operating this workflow. Treat every

derivative as new non-approved work and keep the explicit human visual/audio gate before

publication.

## Post-Rescue Planning

Use the matching `video_*` MCP tool, flat CLI command, or `Client` method when the request

needs semantic retrieval, ordinary cleanup edits, subject-aware transforms, restoration,

composition, creative coordination, or remote egress. Pass JSON-compatible evidence and

intent; present the returned plan and diff before any separate render step.

Never invent source descriptions, hide uncertainty, infer approval from a plan, or treat a

missing local executor as permission to use a cloud provider. Remote work requires a separate

egress manifest and approval. A planner that lacks evidence or capability must abstain.

## Layered Compositing

Use `composite-layers` / `video_composite_layers` when the edit is an ordered stack of image, video, or solid layers, especially lower thirds, picture-in-picture variants, blurback plates, masks/mattes, or platform-specific layout variants.

Prefer this path over raw FFmpeg filtergraphs when an agent needs transforms, opacity, start/duration windows, mask/matte alpha sources, or a receipt that can be reviewed before publishing.

Plan-first flow:

1. Write a JSON spec with `canvas`, ordered `layers`, and explicit output.

2. Run `kino composite-layers --spec layers.json --dry-run --save-layer-plan layer-plan.json`.

3. Inspect the layer plan for source hashes, filtergraph hash, transforms, rotation/pivot, blend modes, timing windows, and masks.

4. Render only after the plan looks right.

5. Run `video-quality-check`, `storyboard` or `thumbnail`, and `video_release_checkpoint`.

The compositor supports allowlisted **full-canvas and positioned** blend modes (`multiply`, `screen`, `overlay`, `darken`, `lighten`) and **rotation** with a `pivot` reference point; the `layer_plan` receipt is v2. Positioned non-`normal` blend requires explicit `width` and `height`, an integral nonnegative in-canvas `position`, full opacity, and no scale, rotation/pivot, mask/matte, or timing window. It crops the running base, blends the same-size layer, and overlays the result back. Full-canvas blend remains supported; other blend geometry fails closed with `unsupported_blend_geometry`. The receipt uses existing per-layer `position` and `transform` fields plus additive `features.positioned_blend`. Output is video-only, and `anchor` remains a position alias distinct from `pivot`. Still deferred and fail-closed: other positioned/scaled/masked/timed blend combinations, rotation + mask, per-layer effect routing, audio compositing, and full NLE adapters. Do not use `composite-layers` as a full NLE replacement.

## Agent Workflow Engine

When the edit is a multi-step job (not a single tool call), use the workflow engine to plan, validate, render, recover, and prove it from one JSON job-spec — through `video_workflow_*` (MCP), `workflow-*` (CLI), or `Client.workflow_*` (Python). Ops are a small allowlist (`probe | trim | resize | convert | merge | add_text`) mapped 1:1 to vetted engines; media references are symbolic (`@sources.*`, `@work/*`, `@outputs.*`) and workspace-confined; everything fails closed. See `../../docs/WORKFLOWS.md`.

Plan → validate → render → inspect → resume:

1. `workflow-validate --spec job.json` — cheap structural gate; renders nothing.

2. `workflow-plan --spec job.json --save-plan plan.json` — dry-run op graph + source probes/hashes; renders zero media.

3. `workflow-render --spec job.json --save-receipt receipt.json` — execute sequentially; emit a provenance receipt (per-step hashes, cleanup manifest, determinism caveat). Add `--all-variants` for batch variants.

4. `workflow-inspect --receipt receipt.json` — read-only integrity re-check + human-review pointers before trusting a receipt.

5. `workflow-render --spec job.json --resume receipt.json` — resume a job that failed with intermediates kept (fail-closed on a changed spec).

Receipts store workspace-relative paths only — keep specs and example receipts free of home paths, usernames, and tokens.

## Workflow

1. Inspect the input first: `kino info <file>` or the MCP/Python equivalent.

2. Make a low-risk plan: trim, resize, normalize audio, subtitles, overlays, effects, or Hyperframes render.

3. Prefer previews or dry-run manifests before expensive or destructive exports:

- `preview` for quick visual review.

- `repurpose-plan` before `repurpose`.

- Hyperframes `inspect`, `snapshot`, or `still` before full render.

- For saved shorts plans: `shorts-plan-show` → `shorts-review` → `shorts-render` → `shorts-package`.

- For thin sound: `sound-capabilities` then `sound-plan-validate` / `sound-voice-batch` / `sound-mix-render` / `sound-qa-loudness` / `sound-qa-asr` (or `kino sound <action>`).

- Real ASR uses a hashed audio/reference request and explicit root; retain its transcript ZIP and report mismatches honestly. Cached local Whisper only; no automatic downloads. Legacy hash-only calls are simulations. See `docs/SOUND_ASR_REQUESTS.md`.

- For actual local EN/ES caption speech, supply a hashed `SoundDubRequest` and explicit project root to `sound-voice-batch`; see `docs/SOUND_DUB_REQUESTS.md`. This optional eSpeak NG path retains WAVs and a mix request. It does not translate, clone voices or apply mastering; legacy plan mode remains a labelled synthetic demo.

- For supplied-media mixing, pass a persisted request plus explicit project root to `sound_mix_render`, or use `sound-mix-render --request-json request.json --project-root .`. Verify the ZIP receipt and decoded media; assembly is not loudness mastering or human listening acceptance. See `docs/SOUND_MIX_REQUESTS.md` for format, filesystem, cancellation and resource limits.

- Cue in/out points select source samples before placement and crossfades; post-roll must remain inside that selection. Verify `source_windows` in the receipt. A ducked bed adds to existing ambience clips.

4. Produce release artifacts before publishing:

- `video-quality-check`

- `storyboard` or `thumbnail`

- `video_release_checkpoint` through MCP or `Client.release_checkpoint()` through Python

5. Ask for human visual/audio review before treating generated media as final.

Stream-shorts packages still require a separate listening gate (G004); automation does not close it.

Do not claim full-episode sound completion from the thin S12 public join alone.

## CLI Examples

```bash

kino doctor

kino --format json info interview.mp4

kino trim interview.mp4 -s 00:02:15 -d 45

kino video-ai-transcribe clip.mp4 --output captions.srt

kino subtitles clip.mp4 captions.srt

# subtitles accept .srt, .vtt, or authored .ass; SRT/VTT render dimension-aware.

# Add --style "FontSize=24,PrimaryColour=&H00FFFFFF&" to override force_style;

# omit --style to preserve an authored .ass file's PlayRes, styles, and positions.

kino resize clip.mp4 --aspect-ratio 9:16

kino composite-layers --spec layers.json --dry-run --save-layer-plan layer-plan.json

kino composite-layers --spec layers.json -o composite.mp4 --save-layer-plan layer-plan.json

kino video-quality-check clip.mp4

kino repurpose-plan clip.mp4 --platforms youtube-shorts instagram-reel tiktok

kino repurpose clip.mp4 --platforms youtube-shorts instagram-reel tiktok

# Saved-plan stream shorts (after a plan exists under PLAN_DIR):

kino shorts-plan-show PLAN_DIR --format json

kino shorts-review PLAN_DIR --candidate-id candidate_01 --decision approve

kino shorts-render PLAN_DIR --candidate-id candidate_01

kino shorts-package PLAN_DIR --candidate-id candidate_01

# Thin sound public join (local-first; not full-episode completion):

kino --format json sound-capabilities

kino --format json sound plan-validate

kino --format json sound-voice-batch

kino --format json sound-qa-loudness

```

## Python Example

```python

from kinocut import Client

video = Client()

plan = video.composite_layers(

"layers.json",

output="composite.mp4",

save_layer_plan="layer-plan.json",

dry_run=True,

)

```

## MCP Setup

```json

{

"mcpServers": {

"kinocut": {

"command": "uvx",

"args": ["--from", "kinocut", "kino"]

}

}

}

```

## Guardrails

- Do not publish or hand off media without a quality check and human review.

- Prefer structured Kinocut tools over raw FFmpeg shell commands; use `composite-layers`/`video_composite_layers` for ordered layer stacks instead of hand-written filtergraphs.

- Keep output paths explicit so generated media is easy to inspect.

- For Hyperframes, verify project structure and rendered snapshots before full video export.