AgentSkillsCN

kuavi-deep-analyze

通过并行分片与缩放功能，开展深度多轮次视频分析。

SKILL.md
--- frontmatter
name: kuavi-deep-analyze
description: Deep multi-pass video analysis with parallel sharding and zoom
agent: video-analyst
context: fork
argument-hint: <video-path> <question>
disable-model-invocation: true

KUAVi Deep Analyze

Perform comprehensive, multi-pass video analysis with parallel temporal sharding and progressive zoom.

Instructions

  1. •Parse $ARGUMENTS for: video path and question/task.
  2. •Index: If the video is not yet indexed, call kuavi_index_video.
  3. •Orient: Call kuavi_get_scene_list to understand the video structure.
  4. •Parallel Shard Analysis: Call kuavi_analyze_shards with the question to get per-shard answers from parallel LLM workers. Use this to identify which temporal regions are most relevant.
  5. •Pass 1 — Visual Search: Use kuavi_search_video across multiple fields (summary, action, visual) to find relevant segments. Cross-reference with shard analysis results.
  6. •Pass 2 — Transcript Search: Use kuavi_search_transcript and kuavi_get_transcript to find spoken evidence. Note any discrepancies with visual findings.
  7. •Pass 3 — Cross-Reference: For key findings, use the 3-pass zoom protocol:
    • •Level 1 zoom to locate
    • •Level 2 zoom to read
    • •Level 3 zoom to confirm specific values
  8. •Pixel Analysis: When counting, measuring, or comparing, use pixel tools (crop_frame, diff_frames, threshold_frame, frame_info) for deterministic evidence.
  9. •Code Reasoning: Use kuavi_eval for complex computations, iterating over frames, or chaining multiple operations.
  10. •Budget Check: Monitor kuavi_get_session_stats — synthesize after 15 tool calls or 120 seconds.
  11. •Synthesize: Combine all evidence into a comprehensive, timestamped answer.

Arguments

The first argument is the video path. Remaining text is the question.

Example: /kuavi-deep-analyze /path/to/video.mp4 What are the key events and when do they occur?