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# AI Video Evaluation Checklist: From Brief to Accepted Clip

By [howard hua (@howardh3)](https://listium.com/@howardh3)

16 views · 0 likes · 0 followers  
Published 4 September 2026 · Updated 4 September 2026

Category: technology & computing

An original planning checklist from FreyaVideo for small AI video comparisons. AI-generated with human-directed scope and source review; this is a proposed evaluation method, not completed tests or a model ranking. The three background guides linked below are published by FreyaVideo. H3 Max is not currently integrated into FreyaVideo (September 4, 2026). Make your own copy and record actual observations before choosing a default model. Cover: an AI-generated illustration, not an output sample or measured comparison.

## Items

### 1. [Define one usable clip before generating](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/0/define-one-usable-clip-before-generating)

Item ID: `0`

- Notes: Write the delivery format and a short acceptance rule. For a product shot, specify which shape, movement, framing and audio details must remain correct. A fast result that misses the brief is not an accepted result. Evidence to save: Brief, target format, acceptance checklist and reviewer.
- Background guide: -

### 2. [Freeze the exact model route and settings](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/1/freeze-the-exact-model-route-and-settings)

Item ID: `1`

- Notes: Record the provider, model version, tier, duration, resolution and audio choice. A family name alone is insufficient. The linked guide compares H3 Max with Kling 3.0 Standard on fal, not every Kling offering. Evidence to save: Route ID, settings, dated pricing source.
- Background guide: Link

### 3. [Prepare a repeatable first-shot brief](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/2/prepare-a-repeatable-first-shot-brief)

Item ID: `2`

- Notes: Use an image you have permission to use, keep its crop consistent, and describe one subject and one motion. Save the original prompt before revising it. Treat a tutorial preset as a starting hypothesis, not proof of quality. Evidence to save: Input reference, crop, original prompt and revisions.
- Background guide: Link

### 4. [Set a small equal attempt budget](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/3/set-a-small-equal-attempt-budget)

Item ID: `3`

- Notes: Choose an affordable maximum number of attempts per route before starting. Alternate routes when practical and note differences in resolution or feature support. Do not call different workloads identical. Evidence to save: Attempt allowance and acknowledged setting differences.
- Background guide: -

### 5. [Keep interactive wait separate from finished-work time](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/4/keep-interactive-wait-separate-from-finished-work-time)

Item ID: `4`

- Notes: Record submission to first actual playback separately from brief to human acceptance. The second includes review and revisions. Backend inference does not include every step of the customer's wait; use the linked speed guide as background, not benchmark results. Evidence to save: Submission, first playback, review and acceptance observations.
- Background guide: Link

### 6. [Label the clocks you actually observed](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/5/label-the-clocks-you-actually-observed)

Item ID: `5`

- Notes: A browser-observed completion includes status-polling and network delay. Provider inference is a separate metric with its own definition. Do not subtract unsynchronized server and browser timestamps, or raw performance.now values from different page loads. Evidence to save: Clock source, document/session identifier, metric definition.
- Background guide: -

### 7. [Preserve failed, rejected and unfinished attempts](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/6/preserve-failed-rejected-and-unfinished-attempts)

Item ID: `6`

- Notes: Give every attempt its own record. Distinguish provider failure from a local observation timeout and from human rejection. Missing durations stay unknown, not zero. Check an existing job's status before paying for a duplicate request. Evidence to save: Attempt ID, outcome, reason, observed duration or unknown.
- Background guide: -

### 8. [Review the output against the original rule](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/7/review-the-output-against-the-original-rule)

Item ID: `7`

- Notes: Check subject consistency, motion, framing and any required speech or sound. Record what failed rather than changing the acceptance rule after seeing a favorite result. Illustrations or provider demos are not substitutes for your own test outputs. Evidence to save: Accepted or rejected, specific reason and reviewer.
- Background guide: -

### 9. [Calculate cost per accepted clip](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/8/calculate-cost-per-accepted-clip)

Item ID: `8`

- Notes: Divide the total actual charged cost of all attempts by the number of accepted clips. Include rejected paid takes and account for confirmed refunds. If none are usable, report no accepted clip instead of a zero cost per success. Evidence to save: Actual charges, refunds, accepted count and calculation.
- Background guide: -

### 10. [Make a scoped decision and retain the evidence](https://listium.com/@howardh3/149384/ai-video-evaluation-checklist-from-brief-to-accepted-clip/9/make-a-scoped-decision-and-retain-the-evidence)

Item ID: `9`

- Notes: Summarize completed waits alongside failed and unfinished counts. A tiny sample can guide a next experiment, not establish a universal fastest model. Keep the brief, settings and observations so a later default change can be explained. Evidence to save: Local conclusion, limits, remaining uncertainty and next experiment.
- Background guide: -