Borrowing it
Nothing to install: this file belongs to jordanurbs/venice-video-harness. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jordanurbs/venice-video-harness/main/.agents/commands/qa-storyboard.mdgit clone --depth 1 https://github.com/jordanurbs/venice-video-harnessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/jordanurbs/venice-video-harness/qa-storyboard)<a href="https://agentmods.dev/commands/jordanurbs/venice-video-harness/qa-storyboard"><img src="https://agentmods.dev/badge/commands/jordanurbs/venice-video-harness/qa-storyboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/jordanurbs/venice-video-harness/qa-storyboard"><img src="https://agentmods.dev/badge/commands/jordanurbs/venice-video-harness/qa-storyboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00780 |
| Opus 5 | $0.00000 | $0.00390 |
| Sonnet 5 | $0.00000 | $0.00156 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
qa-storyboard scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run a visual QA analysis on generated storyboard panels for character and setting consistency.
Steps
-
Load the series data:
- Read
output/<series>/series.jsonfor character descriptions, wardrobe, aesthetic - Read
output/<series>/episodes/episode-NNN/script.jsonfor shot descriptions and which characters appear where
- Read
-
Load character reference images:
- Read each character's
front.pngfromoutput/<series>/characters/<name>/front.png - These are the ground truth for what each character should look like
- Read each character's
-
Load all generated storyboard panels:
- Read each
shot-NNN.pngfrom the episode'sscene-001/directory
- Read each
-
For each panel, analyze using vision:
Character Consistency (compare against reference images and character description):
- Hair: color, length, style matches description?
- Face: recognizable as same character across panels?
- Body/figure: matches build description? (bust, physique, etc.)
- Wardrobe: matches character wardrobe description? Colors, style, accessories correct?
- Skin tone: consistent?
Setting Continuity (compare across sequential panels):
- Time of day / lighting consistent?
- Weather consistent? (rain, etc.)
- Location style consistent?
- Color palette matches aesthetic?
Aesthetic Adherence:
- Art style matches locked aesthetic?
- Color grading consistent?
Spatial Continuity (compare against the shot's
blocking, the location'sspatialAnchors, and the nearest prior panel in the same location):- Each character/object on the stated frame side, at the stated depth, facing the stated direction?
- Positions correct relative to the location's named landmarks?
- Screen sides held from the previous same-location panel (no side-swaps)?
- Eyelines / screen direction preserved (180-degree rule)?
- Landmarks (doors, windows, counters, key props) unmoved — no mirroring, vanishing, or rearranging?
-
Rate each panel:
- PASS: Character, setting, and spatial geometry match descriptions
- FLAG-CRITICAL: Character appearance is wrong (wrong hair, wrong outfit, wrong body type) OR a spatial flip that breaks the scene (characters swapped sides, geography mirrored/rearranged vs the previous panel)
- FLAG-MODERATE: Minor drift but recognizable (slightly different shade, small detail off); character on the wrong frame side vs stated blocking; a relocated landmark
- FLAG-LOW: Stylistic variance or small placement deviation within acceptable range
-
Present the QA report to the user:
- Show each flagged panel inline with the specific issues
- Compare side-by-side with reference images when character issues found
- Recommend which panels to regenerate
- Suggest prompt adjustments for flagged panels
-
If user approves regeneration:
- Delete the flagged panel PNGs
- Re-run
storyboard-episode(it skips existing panels, so only deleted ones regenerate) - Or write custom prompts for specific panels that need targeted fixes
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 65 lines · 0 tokens per session scan A c290ac37f153
qa-storyboard is a command published in the GitHub repository jordanurbs/venice-video-harness (30 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 780 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.