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-production-orchestratorgit 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-production-orchestrator)<a href="https://agentmods.dev/skills/moontzai/folderbridge-mcp/narration-production-orchestrator"><img src="https://agentmods.dev/badge/skills/moontzai/folderbridge-mcp/narration-production-orchestrator/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-production-orchestrator"><img src="https://agentmods.dev/badge/skills/moontzai/folderbridge-mcp/narration-production-orchestrator.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 | $0.00548 |
| Opus 5.5 | $0.00000 | $0.00219 |
| Sonnet 5.5 | $0.00000 | $0.00110 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
narration-production-orchestrator 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Narration Production Orchestrator
Use this when the spoken narration/script is already final and the task is to build or rebuild the video around it.
Source-of-truth order
- Final narration text and approved timing/audio are immutable truth.
- User-approved visual style and explicit prohibitions are next.
- Continuity inventory and project-specific asset constraints come next.
- Existing shots are evidence/references only; never force a new plan to preserve old segmentation.
- Workflow convenience, model defaults, and old shot numbers are subordinate.
Pipeline
- Freeze narration and timing. Build a sentence/meaning ledger; each spoken idea must have a visible job.
- Run
continuity-inventoryonce across the whole piece. Freeze recurring characters, places, motifs, spatial rules and reusable visual metaphors before shot writing. - Run
narration-to-storyboard. Split by semantic change, visual focus and model-safe generation duration, not by legacy segment numbers. - Run
shot-specifieron every storyboard unit. Require a start state, visible event, end state and transition anchor. - Run
minimax-h3-prompt-workflow. Choose T2V/I2V/FL2V/R2V per shot, legal frame count, native resolution, references and retake boundary. - Generate a small representative pilot before full production: at least one abstract-concept shot, one continuity-heavy shot and one human/character shot if applicable.
- Run
generated-video-review. Reject semantic mismatch before spending on upscale/subtitles/final assembly. - Only after all accepted shots pass, assemble to the locked narration, then perform technical delivery gates.
Mandatory rules
- Never begin with an arbitrary target such as “42 segments”. The final shot count is an output of narration analysis.
- One visual beat must carry one dominant explanatory function. Decorative spectacle is not a substitute for semantic evidence.
- Repetition is allowed only when it creates deliberate visual grammar. Reusing the same weak metaphor for multiple distinct claims is a failure.
- Use continuity within a narrative space; use a motivated cut when the narration changes conceptual layer. Do not chain every shot only because last-frame chaining is available.
- Do not generate new stills merely because a workflow expects them. First decide whether a keyframe is actually needed.
- Keep low-resolution experiments explicitly labeled as tests. Final generation provenance must state whether it is native or upscaled.
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 · 42 lines · 0 tokens per session scan A 17addf5a79d3
narration-production-orchestrator 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 548 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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