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 linkprint/local-ai-movie-workspace --skill h3-prompt-writinggit clone --depth 1 https://github.com/linkprint/local-ai-movie-workspaceWrote 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/linkprint/local-ai-movie-workspace/h3-prompt-writing)<a href="https://agentmods.dev/skills/linkprint/local-ai-movie-workspace/h3-prompt-writing"><img src="https://agentmods.dev/badge/skills/linkprint/local-ai-movie-workspace/h3-prompt-writing/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/linkprint/local-ai-movie-workspace/h3-prompt-writing"><img src="https://agentmods.dev/badge/skills/linkprint/local-ai-movie-workspace/h3-prompt-writing.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 | $0.00082 | $0.00599 |
| Opus 5.5 | $0.00033 | $0.00240 |
| Sonnet 5.5 | $0.00016 | $0.00120 |
| Haiku 4.5 | $0.00008 | $0.00060 |
Grade A, and why
h3-prompt-writing 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 2mo 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.
What it actually says
H3 Prompt Writing
Workflow
- Identify the input mode: T2VA, I2VA, FL2VA, L2VA, or full-reference Ref2VA.
- For base text/keyframe modes, read
references/base-en.txtand follow its final prompt structure. - For full-reference mode, read
references/ref-en.txtand follow its six-section rewrite format. - Preserve the exact field names, section order, labels, and timing notation from the selected guide.
Base Modes
- T2VA: build the full audiovisual timeline from text.
- I2VA: start from the first frame and develop forward from it.
- FL2VA: describe the continuous path between the first and last frames.
- L2VA: infer a plausible opening and converge to the supplied last frame.
Use integrated_multimodal_description, overall_soundscape, and non_diegetic_music in the order shown in references/base-en.txt.
Full-Reference Mode
Ref2VA rewrites use subject_definitions, summary, retention_analysis, detailed_description, overall_soundscape, and non_diegetic_music in that order. Reference labels stay consistent across all sections.
Read references/ref-en.txt for label rules, retention analysis, and complete examples.
Output Rules
- Write rewrite sections in English; preserve dialogue, lyrics, and visible scene text in their original language.
- Describe each shot by composition, subjects, environment, actions, camera, sound, and the exact point where referenced content appears.
- Avoid plot summaries, unresolved reference labels, and timing that does not match the requested duration.
Tips for Better Results
- Always match the total duration of the description to the requested video length (4–15 seconds).
- Keep reference labels consistent (e.g.
<Picture 1>,<Video 1>,<Audio 1>) across every section. - Prefer concrete visual and audio details over abstract words like "cinematic" or "beautiful".
- When using keyframes (I2VA / FL2VA / L2VA), clearly state how the first and/or last frame connects to the timeline.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 41 lines · 82 tokens per session scan A a7000443588c
h3-prompt-writing is a skill published in the GitHub repository linkprint/local-ai-movie-workspace (1 stars, last pushed 2mo ago), licensed MIT. It adds 82 tokens to every session and 599 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
h3-prompt-writing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| h3-prompt-writinglinkprint/local-ai-movie-workspace | Skill | 1 | 2mo ago | MIT | A | 82 | Codex |
| higgsfield-seedanceOSideMedia/higgsfield-ai-prompt-skill | Skill | 875 | 14d ago | MIT | A | 100 | Claude Code |
| higgsfieldOSideMedia/higgsfield-ai-prompt-skill | Skill | 875 | 14d ago | MIT | A | 170 | Claude Code |
| higgsfield-actingOSideMedia/higgsfield-ai-prompt-skill | Skill | 875 | 14d ago | MIT | A | 165 | Claude Code |
| higgsfield-promptOSideMedia/higgsfield-ai-prompt-skill | Skill | 875 | 14d ago | MIT | A | 56 | Claude Code |
| higgsfield-seedance-2-5OSideMedia/higgsfield-ai-prompt-skill | Skill | 875 | 14d ago | MIT | A | 194 | Claude Code |
| higgsfield-assistOSideMedia/higgsfield-ai-prompt-skill | Skill | 875 | 14d ago | MIT | A | 56 | Claude Code |