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 blitzreels/agent-skills --skill blitzreels-generationgit clone --depth 1 https://github.com/blitzreels/agent-skillsWrote 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/blitzreels/agent-skills/blitzreels-generation)<a href="https://agentmods.dev/skills/blitzreels/agent-skills/blitzreels-generation"><img src="https://agentmods.dev/badge/skills/blitzreels/agent-skills/blitzreels-generation/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/blitzreels/agent-skills/blitzreels-generation"><img src="https://agentmods.dev/badge/skills/blitzreels/agent-skills/blitzreels-generation.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 | $0.00036 | $0.00704 |
| Opus 5 | $0.00018 | $0.00352 |
| Sonnet 5 | $0.00007 | $0.00141 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
blitzreels-generation 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 6d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BlitzReels Generation
Route generation requests through the current public contract. Full faceless video generation is public; standalone AI Studio media may still require the dashboard.
Workflow
- Load
https://www.blitzreels.com/api/capabilities.jsonand identify the requested generation branch. This step is complete when the public operation or exact dashboard fallback is known. - Inspect only the matching OpenAPI operations and read their current models, limits, and cost guidance. This step is complete when every planned request field is accepted by the current schema.
- For a full faceless video, read
references/faceless-workflow.mdandreferences/faceless-prompting.mdbefore creating the plan. This step is complete when the accepted script and every public operation needed for the run are known. - For a topic, draft the complete narration first; for supplied narration, retain the user's wording. This step is complete when the narration and visual cues are ready for immutable planning.
- Create the project with a caller-generated idempotency key, then create its faceless production plan. This step is complete when the project id, revision id, immutable narration, scene prompts, and cost estimate exist.
- Present the plan, factual-review notes, and cost before paid generation. After approval, generate character anchors and keyframes, then poll the returned job to a terminal state.
- Inspect every generated asset against its atomic shot contract. Revise prompts or regenerate targeted assets until every keyframe is approved or its exact mismatch is reported.
- After approval for animation cost, animate the approved assets and poll the job to a terminal state. Inspect the project timeline, narration joins, generated clip endings, warnings, and media processing state.
- After approval for export cost, export and verify the downloadable output. Completion requires preview evidence for every scene plus the final export status.
What ships with it
4 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.
- 6d ago Changed · +2 lines 4baaa059591b
- 10d ago First seen · 54 lines · 36 tokens per session scan A d72a2bcc748d
blitzreels-generation is a skill published in the GitHub repository blitzreels/agent-skills (3 stars, last pushed 10d ago), licensed MIT. It adds 36 tokens to every session and 704 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
authoring-video-templates
Use when creating or editing a video template JSON (the template descriptor), adding or changing sections/filters/maps/variables/transitions/looks/motion/audio/layers, or debugging template validation errors in ffmpeg-video-composer.
core-architecture-patterns
Use when adding a segment type, platform adapter, editor manager, core service, or descriptor effect (look/grade/motion/section-audio field) in packages/ffmpeg-video-composer, or when wiring new dependencies into the tsyringe container.
ondevice-ffmpeg-engine
Use when building, modifying, or consuming the on-device FFmpeg engine — the Rust crate packages/ffmpeg-engine, the leclap-ffmpeg Expo native module, the run/probe/version/cancel API, the uniffi bindings, build-engine.sh, or the FFmpeg-from-source toolchain in scripts/ffmpeg.
cross-platform-ffmpeg
Use when working with FFmpeg across Node/Static/WASM, the PlatformBridge, the FFmpeg detection/fallback chain, or browser/React Native runtime constraints in ffmpeg-video-composer.
kling-studio
Full-featured Kling 3.0 Omni video generation skill. Covers text-to-video, image-to-video, video editing (base mode), video reference (feature mode), multi-shot generation, and audio-synced video. Includes validated API constraint rules and prompt engineering guide.
seedance-prompt
This skill should be used when the user asks to write, improve, translate, compress, or debug a Seedance 2.0 video prompt; mentions T2V, I2V, V2V, R2V, camera direction, prompt quality, or provides reference assets for a production-ready prompt.