Turn authorized current builds, workflows, dashboards, analytics, and completed work into proof-led founder videos, then rank and combine the strongest filmable artifacts into exact 15-minute long-for…
Library skill — the default version is maintained in GitHub; edits you make live in your own clone.
Turn real work into videos whose opening promise is repaid by a visible artifact, workflow, result, or before/after.
From the repository root, run the privacy-preserving version check and telemetry initializer when available:
python3 telemetry/version_check.py 2>/dev/null || true
python3 telemetry/telemetry_init.py 2>/dev/null || true
Remote telemetry is opt-in. Never log content, URLs, paths, credentials, names, business data, or proof artifacts.
State the authorized sources, owner, channel, viewer, runtime, deliverable, and stop condition. Keep source systems read-only. Never search unrelated accounts, repositories, conversations, or credentials.
Ask the user to rank these outcomes when not already known:
Load any supplied creator voice guide before writing titles or hooks. Reject packages that violate it even if their numeric scores pass.
Inspect only supplied or authorized builds, repositories, demos, agent runs, dashboards, analytics, and workflow outputs. For every candidate record:
Do not upgrade remembered results into verified evidence. Label provisional candidates.
Read references/selection-rubric.md. Reject or repair a candidate unless:
Framework-only topics must use real case studies. Product walkthroughs must lead with the viewer outcome rather than a feature list.
Combine ideas only when they share one mechanism, viewer, and payoff. Examples include sales and recruiting workflows that use the same outreach loop, multiple cost controls inside one audit system, or a demonstrated content result paired with the loop that produced it.
Do not combine unrelated proof points merely to reach the runtime. Route thin ideas to shorter formats.
Use 900 seconds unless the user overrides it:
0:00-0:30 show the outcome and promise;0:30-2:00 establish the stakes and baseline;2:00-5:00 show what was built;5:00-10:00 demonstrate how it works;10:00-13:00 show receipts, limitations, and lessons;13:00-15:00 give the implementation path and close the promise.Use the nine episode lenses in references/selection-rubric.md. Require a 90+ average, with Demoability and Payoff Integrity each at least 90.
Create exactly three materially different packages:
Require every package to score at least 9.0/10 with no dimension below 8.5. Use zero to four thumbnail words and no more than three major visual groups. Prefer the real artifact, result screen, dashboard, output, or physical prop over an abstract metaphor.
After the slate passes, use content-eval for deeper panel review, video-content-engine for the production plan, and shortform-idea-grill for complete short-form derivatives when those skills are installed. Use a compatible thumbnail-packaging skill when available. Keep achieved results distinct from plans and forecasts.
Read references/output-contract.md, save the structured slate as JSON, and run:
python3 scripts/evaluate_slate.py slate.json --output slate-eval.json
python3 scripts/evaluate_slate.py slate.json --validate-only
The validator checks runtime, artifact evidence, claim proof, episode scores, packaging lanes, thumbnail word count, component budget, and package score floors.
Return the ranked slate, combination decisions, exact run of show, first-30-second promise, proof and pickup ledger, three packages per episode, evaluation readback, winning package, and shoot order.
Separate ready from repair. A strong package never overrides missing proof. Do not render, publish, schedule, upload, or change a live asset without explicit approval.