review-video-with-pingfusi

name

review-video-with-pingfusi

description

Have a rendered video reviewed by a real human against the prompts that produced it, through iterative pingfusi review rounds. Use when asked to "review this video", "check the rendered video", "does this video match the prompt/brief", or after rendering a Remotion composition or AI-generated clip that no test can judge. Do not use for web pages (use fix-with-pingfusi or beautify-with-pingfusi) or for pixel-matching a site (use pixel-perfect-clone).

Review a video with pingfusi

A machine can render a video; it cannot tell you whether the result lands the brief. This skill puts the render in front of a real human reviewer who scrubs it, pins comments to exact timestamps, draws on frames, and returns a verdict — then you fix the source, re-render, and refile until the verdict is Matches the prompt.

Non-negotiables

• Publish before review. The reviewer is remote: video_url must be a public, long-lived MP4 whose host answers Range requests with 206 + Content-Range (the service probes it at file time and refuses the round otherwise). A new render is a new URL — never mutate the bytes behind a URL a round already cites.
• The brief must be honest. current_brief is what the video must match NOW. Superseded prompts go into prompt_history marked replaced — never silently dropped; the reviewer resolves conflicts by state, not guesswork. requirements are concrete, checkable claims, each naming the prompt_ids it came from.
• Video rounds have a fixed public shape. The service supplies the questionnaire and the verdict pair Matches the prompt / Needs another pass; authored steps, instructions, and verdict_options are web-only. The richness goes into the brief, history, and requirements, which the reviewer sees on claim.
• Act on feedback in the SOURCE. A timestamped comment means a fix in the composition code, the prompt, or the asset that produced that moment — never a hand-patched frame or a trimmed clip to dodge the note.
• Never approve your own render, and never infer approval from prose. Done is a fresh core.review.verify(stateFile) returning ok === true on the declared verdict.

Workflow

1. Run pingfusi doctor. If the review login is missing, stop and have the user run pingfusi setup; there is no offline substitute for a human verdict.

2. Assemble the review context before rendering anything final: every prompt in authored order (active / replaced / context), the distilled current_brief, and requirements with prompt provenance. The complete context caps at 250 KB.

3. Render the MP4 and publish it through Pingfusi hosting by default:

   pingfusi publish <render.mp4> --name <name>-round-1 \
     --record .pingfusi/video/<name>/round-1.json --json
   

   The command creates the player wrapper, uploads immutable bytes, and returns a direct asset_url; use that value as video_url. Pingfusi serves it with 206 and Content-Range, so the native player can scrub. The current hosted-video cap is 25 MB per render. If a render cannot fit after reasonable encoding, use another long-lived public host that serves Range requests; do not introduce a live-site tunnel for a file.

4. File the round against a caller-owned state file:

   const core = require("pingfusi/packages/core");
   const { ping_id } = await core.review.file(stateFile, {
     media_type: "video",
     video_url,
     current_brief,
     prompt_history,  // [{ id, text, state: "active"|"replaced"|"context", replaced_by? }]
     requirements,    // [{ id, text, prompt_ids }]
     n_target: 1,
     approve_verdicts: ["Matches the prompt"], // local bookkeeping, stripped before the wire
   });
   

   url and draft_url must be absent — video mode refuses them.

5. The filing command automatically chains client-safe wait legs until feedback. If a raw MCP leg returns pending, immediately call pingfusi_wait again; never return pending to the user or file a duplicate. Each leg renews the short idle lease; passive result/verify reads do not. When results land, read the envelope: comments arrive sorted by video_anchor.time_ms, drawn annotations in normalized frame coordinates (0 = left/top, 1 = right/bottom), questionnaire answers attached to their questions. Fix every noted moment in the source, re-render, publish the NEW file under a new receipt/URL, and refile with the same context — update current_brief/requirements only if the user's ask actually changed.

6. Repeat until core.review.verify(stateFile) returns ok === true on Matches the prompt. Record the receipt; stop only on approval or when the user says stop.