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calesthio 50891a75b7 hyperframes: add HTML/CSS/GSAP as a parallel composition runtime

Separates creative grammar (renderer_family) from technical engine
(render_runtime) so HyperFrames can stand alongside Remotion as a
first-class runtime instead of masquerading as a Remotion sub-case.
Locks runtime choice at proposal stage and enforces it end-to-end: the
schemas require it, video_compose routes by it, the reviewer fails
closed on silent swaps, and a parametrized contract test walks every
pipeline manifest to ensure each planning-stage skill explains the
conversation to the user. Adds hyperframes_compose (scaffold/lint/
validate/render/doctor/add_block), a playbook -> CSS style bridge, and
vendored HyperFrames Layer 3 skills from commit d291358, pinned via
PROVENANCE.md for future re-sync. Final_review now records
render_runtime_used and runtime_swap_detected so compose lies are
catchable after the fact.

2026-04-18 18:37:00 -07:00

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Idea Director - Clip Factory Pipeline

When To Use

Use this pipeline when the source is long-form footage and the goal is multiple short-form deliverables: webinar clips, interview cuts, livestream highlights, keynote excerpts, or presentation snippets.

You are not planning one video. You are planning a ranked portfolio of clips.

Runtime Selection (MANDATORY — present the constraint, don't silently pick)

Lock render_runtime = "remotion" (for composed clips with word-level captions) or "ffmpeg" (for pure concat/trim with no composition). HyperFrames is NOT a valid runtime on this pipeline in Phase 1 — clip-factory depends on Remotion's word-level caption burn, which has no HyperFrames parity yet.

Per AGENT_GUIDE.md → "Present Both Composition Runtimes (HARD RULE)": do NOT silently lock remotion. Surface the constraint to the user: "HyperFrames is an available runtime on your machine, but clip-factory depends on Remotion caption burn that doesn't have HyperFrames parity yet, so remotion is the only viable choice here — OK to proceed?" Record the decision in decision_log with category render_runtime_selection, including hyperframes as a rejected option (rejected_because: "caption-burn parity deferred on clip-factory").

Reference Inputs

docs/clip-factory-best-practices.md
skills/creative/short-form.md
skills/creative/video-editing.md

Process

1. Understand The Source And The Goal

Capture the source shape:

webinar
interview
panel
keynote
stream
customer story

Then capture the business goal:

awareness
thought leadership
lead generation
product education
event recap

2. Choose A Clip Portfolio Strategy

A good batch mixes clip types instead of extracting the same energy repeatedly.

Common clip families:

hook: surprising claim or strong cold open
insight: useful takeaway or lesson
story: narrative moment with emotional shape
proof: stat, case study, demo result
opinion: hot take, disagreement, contrarian point

Use the brief metadata to define the intended balance across those families.

3. Set Yield Targets Realistically

Guideline ranges:

15-30 min: 3-6 strong clips
30-60 min: 5-10 strong clips
60+ min: 8-15 strong clips if the source quality supports it

Do not inflate clip count to satisfy a round number. A smaller strong batch beats a padded weak batch.

4. Map Platforms Before Extraction

Plan platform fit early:

9:16 for Shorts, Reels, TikTok
1:1 for LinkedIn and safer feed repurposing
16:9 when slides, demos, or wide context matter

If the source framing clearly will not survive vertical crops, say so in the brief metadata now.

5. Build The Brief

Keep the schema-level brief concise and put the richer batch plan in brief.metadata.

Recommended metadata keys:

source_type
source_duration_seconds
clip_target_range
clip_families
primary_platforms
secondary_platforms
selection_criteria
known_visual_constraints
distribution_goal

6. Quality Gate

the clip count target is realistic,
the platform mix matches the content,
the brief defines ranking criteria before extraction starts,
the agent has acknowledged any obvious reframing limits.

Common Pitfalls

Planning a batch around quantity before quality.
Assuming every source can produce vertical clips cleanly.
Treating all clips as interchangeable instead of intentionally varied.
Starting extraction without defining what "good" means for this batch.

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