agentleFS
AnayDhawanAnayDhawan/openvidstudio/.cursor/skills/supernova/SKILL.md

supernova

Skill33 starsChanged 14 days agoApache-2.0View on GitHub

Use when making a short animated STEM lesson video (a maths, physics or computer science concept explained in up to two minutes, vertical, narrated) with openvidstudio, or when the user says "Supernova", "lesson video", "explain this concept as a reel" or "teaching video". Script first, always the same seven-beat arc, built from a concept card and a derived-and-verified script, then voice, scenes, review and finalize. Not for product demos (use openvidstudio or openvidstudio-director).

  • Installs packages

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 0 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Write src/videos/<name>/concept.json: goal, terms (the two or three that need defining), example (the one worked example, with its real …

    line 38
  2. Very specific:

    Write derivation.md first: one line per step with its reason, the assumptions, one place the result fails.

    line 45
  3. Very specific:

    Fit the beats to the voice: run fit_beats (dryRun: true first if you want to see the lengths).

    line 57
  4. Very specific:

    Instead of Remotion scenes, the visuals can be one HTML canvas file: hand-written, built on the pixel narrator and depth kit in …

    line 75

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

supernova

How to make a lesson video, in order. A lesson is one concept in up to two minutes at 1080x1920, narrated and captioned, and every lesson has the same shape. The script is the product; the visuals illustrate it. Read docs/SUPERNOVA.md (design system, primitives, voice, captions) and docs/SCRIPT.md (the arc and the rules) before step 3.

Everything in a lesson is constructed on purpose, so nothing here is footage and nothing is captured. The numbers on screen are computed by code from the concept card's worked example, never typed from memory.

The arc (constant)

This is the default, seven-beat arc. A concept card with "arc": "story" is the story-first lesson instead (a situation told as a problem, the idea, the formulas, the formulas applied, one watch out, a practice question to answer in the comments): its six beats, extra card fields and story-* checks are in docs/SCRIPT.md#the-story-arc.

Hook, picture, set up, derive, use it, aha, close. In that order, every lesson. Times for 120 s are in SCRIPT.md.

  1. Hook: a beginner's question or a surprising fact in sentence one. Then say where the lesson sits (the card's referenceSpoken: a chapter code or "Part 2 of 4").
  2. Picture: the diagram starts here, before any formula, inside the first 15 s. Everyday words; define each term at first use.
  3. Set up: symbols, units, assumptions, drawn on the diagram.
  4. Derive: the formula built line by line with one Derivation: a step per line, each with its spoken form and a because, each step justified.
  5. Use it: one worked example with the real numbers and units.
  6. Aha: the result that generalises or surprises, and where it stops being true.
  7. Close: one-line recap, then the check question. End on the question; hold the last frame.

1. Set up

  • init_project with mode: "supernova" (and the lesson's name). It stores production.mode, makes the frame 1080x1920, and installs @openvidstudio/stem with its fonts and the maths renderer.
  • preflight once. Its edge-tts check speaks one word, so a refused connection (7.2.8 gets a 403) shows up here with the fix, pip install -U edge-tts.
  • plan_production with a time budget (a lesson has no creative level). Show the plan.

2. The concept card

Write src/videos/<name>/concept.json: goal, terms (the two or three that need defining), example (the one worked example, with its real numbers), plus reference and referenceSpoken (where the lesson sits) and maxSeconds (default 120). Decide the subject (math, physics, cs, chemistry, biology: it sets the accent). A big topic is a series; each part ends on the next question.

3. The script, derived and verified

  • Write derivation.md first: one line per step with its reason, the assumptions, one place the result fails.
  • Check the maths with code (plain Python or sympy): the symbolic result, the worked example, the units. Generate the numbers the scenes show from that code. Do not type a number twice.
  • Draft the narration beat by beat to the arc and the rules in SCRIPT.md. Sentences of about 14 words or fewer, maths written as it is spoken, at most two new terms a beat, about 270 to 330 words in all.
  • plan_beats for provisional lengths; validate_beats (2.3 to 2.9 words per second) and check_script (pass beatsJson and conceptCard). Fix every error, read every warning.
  • Show the user the whole script and the derivation and get an explicit yes before any scene is built. Then write_beats_file.

4. Voice

  • generate_narration with the fixed lesson voice from SUPERNOVA.md (edge-tts). It writes word timings per beat.
  • Fit the beats to the voice: run fit_beats (dryRun: true first if you want to see the lengths). It sets each beat to the measured spokenSeconds plus half a second inside the pace window, and lists in unfittable any line to shorten. Then run generate_narration again with overwrite: true. Do not stretch outside 0.9 to 1.12.
  • Done when every beat has a clip, the result reports no overrun, and the lesson is at most maxSeconds.

5. Scenes

  • scaffold_scene in "starter" mode per beat, or write the file by hand. Build each from @openvidstudio/stem (Spark, Nova, Axes, Plot, NumberLine, Equation, Derivation, FreeBody, ArrayViz, LessonCaptions) against the video's design.ts: export const design = supernovaDesignSystem("<subject>").
  • One idea on screen at a time, at most two things moving, one glowing element at a time. The Nova is used once, on the aha. Every Equation and every Derivation step carries a spoken string that appears in its beat's narration, in the order spoken.
  • Key content stays inside the Reels safe zones. Sizes come from useVideoConfig(). Captions: one line per beat, <LessonCaptions beatId="hook" text={vo} /> (see "Captions" in SUPERNOVA.md), so they break at sentence ends.
  • compose_score with percussion: "none" for a quiet pad under the voice. stitch_composition.

5b. Or: the pictures come from a canvas explainer

Instead of Remotion scenes, the visuals can be one HTML canvas file: hand-written, built on the pixel narrator and depth kit in @openvidstudio/styles, or generated by another tool from the prompt in docs/EXPLAINERS.md (which is the whole contract and a working skeleton). The script, voice and fit steps above are unchanged. Then:

  • validate_canvas_explainer with videoName, width: 1080, height: 1920: purity, text sizes, safe areas, the arc and the sound. Fix every error.
  • render_canvas_explainer with the same arguments and async: true, then job_status. beats.json becomes window.BEATS, the narration is mixed in over the score and the beats' text is burned in as captions. Expect 15 to 20 minutes for a busy 90 second lesson.
  • Skip scaffold_scene, stitch_composition and compose_score for this route; the explainer carries its own score. Go to step 7.

6. Review

  • check_script again with the scenes present, then validate_scenes with render: true. Besides framing, numbers and glow it checks the arc: diagram-late (nothing drawn beyond the background and captions by 15 s) and static-stretch (nothing changes for 8 s). Fix both before posting.
  • render_stills and contact_sheet: look at the frames, then render_video, and listen. (A canvas explainer has no stills tool: pull frames from the rendered mp4 with qc_extract_frames.)
  • Done when there are no errors, the diagram starts early, the Nova lands on the aha, and every beat sounds like one person.

7. Finalize

  • finalize_video (it must report no audio-tick). write_description: one line saying the video is a constructed explanation, not footage. If the card has a practiceQuestion and an answer it also adds the question and writes output/<name>-ANSWER.md (the pinned comment), and the config's disclaimers close the description.
  • Done when the final file and the description are in output/.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.