transcreveai-video-intelligence

name	transcreveai-video-intelligence
description	Use to turn video URLs or media files into evidence-backed knowledge dossiers with TranscreveAI. Trigger on Reels, YouTube, TikTok, Loom, Vimeo, X/Twitter video links, local media files, video summaries, dossier requests, RAG over video runs, or requests to use TranscreveAI.

TranscreveAI Video Intelligence

Use this skill when the user sends a video URL/file or asks Codex to extract, summarize, analyze, index, or ask questions about video content with TranscreveAI.

Tooling Preference

• Prefer the TranscreveAI MCP tools when available:
  • sources_probe for source pre-checks.
  • agent_run for the full probe/analyze/index/ask workflow.
  • agent_batch for saved lists of sources.
  • index, ask, runs_list, runs_show, and shared_catalog for retrieval.
• If the MCP tools are not available in the current Codex thread, use the CLI.
• CLI command preference:
  • First try transcreveai.
  • If it is not on PATH, use the plugin wrapper at ./scripts/transcreveai from the installed plugin root.
• MCP server command for local registration:
  • bash ./scripts/transcreveai-mcp --transport stdio from the installed plugin root.
• The plugin wrappers add /opt/homebrew/bin and /usr/local/bin to PATH so Homebrew FFmpeg/Tesseract installs are visible to Codex-launched processes.
• If TranscreveAI is not installed globally, the wrappers create a venv under ~/.cache/transcreveai-codex-plugin and install transcreve-ai[mcp,rag] from pinned commit 7490586e86b57eefae377dc6839e9476f89ffd8d of https://github.com/DeHor-Labs/transcreve-ai.git.

Required Nested Handoff

Whenever TranscreveAI is used as a nested capability for another agent or workflow:

• Keep run_id, out, and index-db identifiable for the caller.
• Use temporary retention by default when the caller only needs extraction, summary, or an answer from YouTube, Reels, TikTok, local media, and similar sources.
• Preserve artifacts or index in the user's real knowledge base only when the caller/user asks to save, index, audit later, or reuse the dossier.
• When durable reuse is requested, run transcreveai share RUN_ID --json or call MCP share_run after analysis. If the run used an isolated index, pass the same --index-db or use transcreveai share --run-dir "$RUN_DIR" --json. It writes handoff.md, manifest.json, knowledge.md, and analysis.json, and updates share-root catalog.json/index.md. To rediscover durable packets later, use transcreveai share --catalog --json or MCP shared_catalog.
• If the dossier is preserved or indexed, explicitly say: O dossie que voce criou foi salvo para voce como conhecimento.
• Include the path to knowledge.md, the run_id, and whether the knowledge was saved in the user's real index or in an isolated agent index.
• If the run was temporary and cleaned up, do not claim it was saved; report the run_id, that the answer was based on generated artifacts, and that temporary files were removed.

Safe Defaults

• For smoke tests, demos, and automated validation, isolate state:
  • --index-db /tmp/transcreveai-agent.db
  • --out /tmp/transcreveai-agent
  • --ai off
  • --provider local
  • --force
• For temporary production-like agent runs, create a dedicated temp directory: TMP=$(mktemp -d "${TMPDIR:-/tmp}/transcreveai-agent.XXXXXX"), use --index-db "$TMP/index.db" and --out "$TMP/runs", read the generated artifacts, then rm -rf "$TMP".
• If a temporary run used the real index, remove it with transcreveai runs rm RUN_ID --force before deleting files.
• Do not expose API keys, cookie contents, or complete sensitive URLs in logs or final answers.
• Use --cookies-browser chrome only for user-owned browser state and only when needed for sources such as Instagram.
• Base final answers on generated artifacts, especially knowledge.md, analysis.json, and template files. Do not create a parallel manual dossier and pretend it came from TranscreveAI.
• If analysis fails before artifacts are written, check whether ffmpeg, ffprobe, and tesseract are visible in PATH before treating it as a TranscreveAI bug.

Recommended Agent Flow

1. Probe the source:

transcreveai sources probe "SOURCE" --json

Read kind, adapter, requires_cookies, and notes. If cookies are required, prefer --cookies-browser chrome for user-owned sources.

2. Run the agent workflow:

TMP=$(mktemp -d "${TMPDIR:-/tmp}/transcreveai-agent.XXXXXX")
transcreveai --index-db "$TMP/index.db" agent run "SOURCE" --out "$TMP/runs" --json

For an isolated no-cost smoke:

transcreveai --index-db /tmp/transcreveai-agent.db agent run "SOURCE" \
  --out /tmp/transcreveai-agent \
  --ai off \
  --provider local \
  --force \
  --json

3. Add templates when useful:

• Use --template content for creator, marketing, product, sales, distribution, or content workflow videos.
• Use --template skill for videos about agents, prompts, skills, Claude, Codex, automations, or reusable workflows.
• Read generated content.md/content.json/content.csv and skill.md/skill.json before answering about those artifacts.

4. Read the evidence:

• Always inspect knowledge.md.
• Inspect analysis.json for structured metadata, source, paths, transcript quality, and run details.
• If the user asks a question over the run, index and query:

transcreveai index RUN_ID
transcreveai ask "QUESTION" --run-id RUN_ID --top-k 8

5. Report compactly:

• Summarize what the video actually supports.
• Separate evidence from inference when making product, business, or technical recommendations.
• Cite artifact paths only when the dossier is preserved. For temporary runs that are cleaned up, cite the run_id and cleanup status instead.
• State limitations when transcript, OCR, visual context, or source access was weak.
• Unless the user asked to preserve/index the dossier, remove the temp directory after reading the artifacts and mention that temporary files were removed.

Batch Flow

For multiple URLs or files:

transcreveai agent batch ./sources.txt \
  --template content \
  --template skill \
  --strict \
  --json

Use --strict when any failed item should block the caller. Read success, ok_count, failed_count, batch.md, batch.json, and per-run template_paths.

Expected Artifacts

• knowledge.md: human-readable dossier.
• analysis.json: structured run metadata and analysis.
• Optional content.md, content.json, content.csv.
• Optional skill.md, skill.json.
• Optional batch.md, batch.json for batch runs.

Example Starter Commands

transcreveai sources probe "https://www.instagram.com/reel/..." --json
transcreveai agent run "https://www.instagram.com/reel/..." --template content --template skill --json
transcreveai agent batch ./sources.txt --template content --template skill --json
transcreveai ask "What decisions does this video support?" --run-id RUN_ID --top-k 8

Palestra tecnica, aula ou tutorial longo

Use --frame-strategy slides: os frames saem na troca de tela em vez de a cada N segundos, entao nenhum slide se perde nem aparece repetido. O padrao auto ja liga isso sozinho quando o video e longo demais para o intervalo cobrir.

transcreveai analyze "<url>" --ai auto --frame-strategy slides

Codigo mostrado na tela e reconhecido e sai em bloco cercado no knowledge.md, com a indentacao reconstruida a partir da posicao do texto na imagem. Em slides os frames sao gravados em PNG: o JPEG borra texto fino e arruina o OCR de codigo.