videodb-query

name	videodb_query
description	Video database query skill for battlefield reconnaissance analysis. Use when analyzing drone footage, detecting military objects (tanks, trucks, soldiers), searching for specific events, or understanding video content. Always call get_contexts action first before other queries.

Video Database Query Skill

Overview

This skill provides comprehensive video analysis capabilities for battlefield reconnaissance. Use it to search for objects, events, and patterns in analyzed drone footage.

Critical Rule: Always Get Contexts First

Before any video query, you MUST call the get_contexts action first:

contexts = videodb_query_skill("get_contexts")
if contexts["status"] == "error":
    # No videos selected - inform user
    final_answer("Please select videos from the Context Catalog tab first.")

Available Actions

1. get_contexts

Get currently selected video and PDF contexts. Always call this first.

result = videodb_query_skill("get_contexts")
# Returns: selected_videos, selected_pdfs, num_videos, num_pdfs

2. get_summary

Get overview statistics for selected videos.

result = videodb_query_skill("get_summary")
# Returns: video names, durations, object counts per video

3. semantic_search

Search video segments using natural language descriptions.

result = videodb_query_skill("semantic_search", query="convoy moving through forest")
# Returns: matching segments with similarity scores

4. object_search

Find segments containing specific object types.

Valid object types: tank, truck, soldier

result = videodb_query_skill("object_search", object_type="tank")
# Returns: timeline_text (pre-formatted), summary_text, max_objects_at_any_point

Important: Use timeline_text and summary_text directly in your response. Never sum object counts across segments - the same object may appear in multiple consecutive segments.

5. event_search

Search by event keywords in AI-generated descriptions.

result = videodb_query_skill("event_search", query="moving")
# Returns: segments with matching descriptions

6. segment_details

Get detailed information about a specific segment.

result = videodb_query_skill("segment_details", segment_id=0, video_ids=["m-abc123"])
# Returns: event_description, object_counts, individual object positions

Temporal Continuity Awareness

Critical Understanding: The same object appearing in consecutive segments is NOT multiple objects. When reporting object counts:

• WRONG: "Found 45 tanks" (summing all detections)
• CORRECT: "Maximum 15 tanks observed at any point, appearing across 3 segments"

The object_search action returns pre-formatted timeline_text that handles this correctly. Use it directly.

Multi-Video Analysis

When multiple videos are selected:

1. Assess relationships: Are videos sequential (same mission) or independent?
2. Attribution: Always specify which video findings come from
3. Counting methodology: Related videos may show same objects

Example Multi-Video Workflow

# Get contexts
contexts = videodb_query_skill("get_contexts")

# Query each video
for video_id in contexts["result"]["selected_videos"]:
    result = videodb_query_skill("object_search", object_type="tank", video_ids=[video_id])
    # Process results per video

# Provide context-aware response

Result Structure

All actions return:

• status: "success", "no_results", or "error"
• action: The action performed
• result: Action-specific data
• message: Human-readable summary

Best Practices

1. Always call get_contexts first
2. Check status before using results
3. Use timeline_text directly for object counts
4. Explain your counting methodology
5. Attribute findings to specific videos
6. Handle "no_results" gracefully (it's not an error)