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 IAPro-Community/Orquestrador-Maestro --skill skill-live-processinggit clone --depth 1 https://github.com/IAPro-Community/Orquestrador-MaestroWrote 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/iapro-community/orquestrador-maestro/skill-live-processing)<a href="https://agentmods.dev/skills/iapro-community/orquestrador-maestro/skill-live-processing"><img src="https://agentmods.dev/badge/skills/iapro-community/orquestrador-maestro/skill-live-processing/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/iapro-community/orquestrador-maestro/skill-live-processing"><img src="https://agentmods.dev/badge/skills/iapro-community/orquestrador-maestro/skill-live-processing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.00608 |
| Opus 5 | $0.00028 | $0.00304 |
| Sonnet 5 | $0.00011 | $0.00122 |
| Haiku 4.5 | $0.00006 | $0.00061 |
Grade A, and why
skill-live-processing 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 9d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Live Processing
Use this skill for live streams, long VODs, and media pipelines that produce transcripts, summaries, clips, thumbnails, captions, or publishable assets.
Pipeline Contract
- Separate ingestion, processing, enrichment, review, and publishing into explicit stages.
- Keep platform OAuth tokens, webhook secrets, storage credentials, AI provider keys, and signing keys server-side.
- Validate source ownership, platform terms, tenant quota, duration, codec, file size, language, and processing options before enqueueing.
- Create a durable
media_jobsrecord before downloading or running expensive work. - Run long work in queues or workers. Do not download, transcode, transcribe, or render inside request handlers.
- Make every stage idempotent and resumable from stored artifacts, checksums, stage status, and provider job IDs.
- Store source media and generated assets in private storage. Use signed URLs with short TTLs for preview and download.
- Batch and chunk AI work. Reuse transcript segments, embeddings, shot boundaries, and thumbnails instead of resending full media context.
- Require review before publishing clips or generated metadata unless the product has explicit auto-publish consent.
- Emit structured progress, queue age, stage duration, retry count, artifact checksums, and sanitized failure reasons.
Stage States
Use stable states such as:
queued, validating, downloading, extracting_audio, transcribing, detecting_clips, rendering, review_ready, publishing, published, failed, cancelled.
Data Model Hints
media_jobs: tenant ID, owner ID, source type, source URL or asset ID, status, current stage, progress, idempotency key, retry count, error class.media_assets: job ID, kind, storage path, duration, size, checksum, codec, metadata, retention deadline.clip_candidates: job ID, timestamps, score, reason, transcript excerpt hash, review status.processing_events: job ID, stage, status, duration, worker ID, details.
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.
- 9d ago First seen · 51 lines · 56 tokens per session scan A 4c0ec9678249
skill-live-processing is a skill published in the GitHub repository IAPro-Community/Orquestrador-Maestro (41 stars, last pushed 3d ago), licensed Apache-2.0. It adds 56 tokens to every session and 608 once invoked, about $0.0003 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 2026-08-30.
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