Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add MoonTzai/folderbridge-mcp --skill narration-to-storyboardgit clone --depth 1 https://github.com/MoonTzai/folderbridge-mcpWrote 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/skills/moontzai/folderbridge-mcp/narration-to-storyboard)<a href="https://agentmods.dev/skills/moontzai/folderbridge-mcp/narration-to-storyboard"><img src="https://agentmods.dev/badge/skills/moontzai/folderbridge-mcp/narration-to-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/skills/moontzai/folderbridge-mcp/narration-to-storyboard"><img src="https://agentmods.dev/badge/skills/moontzai/folderbridge-mcp/narration-to-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 | $0.00515 |
| Opus 5.5 | $0.00000 | $0.00206 |
| Sonnet 5.5 | $0.00000 | $0.00103 |
| Haiku 4.5 | $0.00000 | $0.00052 |
Grade A, and why
narration-to-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 1mo 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Narration to Storyboard
Use only when the narration/script is finalized. The job is to design what the viewer must see while each spoken idea is heard, not to rewrite the narration.
Step 1: Meaning ledger
For every sentence or semantic clause record internally:
- exact spoken text or stable clause ID;
- start/end timing if available;
- claim type: definition, example, contrast, process, question, qualification, conclusion, call-to-action;
- what the viewer must understand by the end of the clause;
- whether the meaning is concrete, relational or abstract.
Step 2: Visual evidence
For each clause answer: “What visible change would prove this sentence has been understood?”
Prefer:
- definition -> establish a stable visual system, then show the defining transformation;
- contrast -> preserve common context while changing only the contrasted variable;
- example -> use a concrete scene whose visible cause/result maps tightly to the words;
- process -> show ordered cause -> transformation -> result;
- probability/distribution -> show population structure and relative recurrence, not decorative glow;
- agency -> show who chooses/acts and who remains a tool/background system;
- conclusion -> recombine established motifs rather than inventing a new metaphor at the end.
Step 3: Find beat boundaries
Split when one of these changes:
- dominant claim or explanatory function;
- subject/observer;
- spatial layer;
- visual metaphor;
- before/after state;
- required camera objective;
- continuity strategy.
Do not split merely because a sentence ends. Do not preserve legacy segment counts.
Step 4: Build generation units
Group adjacent beats when they share scene, continuity and a single model-executable transformation. Split when a unit becomes semantically overloaded, physically contradictory, or exceeds the target model's reliable duration.
Each unit must contain:
- narration range;
- one-sentence visual thesis;
- start state;
- 1–3 dominant visible events;
- end state;
- continuity/transition anchor;
- semantic acceptance criterion: what must be visible for the narration to be considered matched.
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.
- 1mo ago First seen · 60 lines · 0 tokens per session scan A b430477316b5
narration-to-storyboard is a skill published in the GitHub repository MoonTzai/folderbridge-mcp (2 stars, last pushed 25d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 515 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 2026-09-08.
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