Add folder anatomy (scripts/agent.py + references/api-reference.md) for 648 cybersecurity skills

Complete skill folder anatomy across all cybersecurity skills:
- scripts/agent.py: 80-150 line Python agents using real libraries (impacket,
  boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.)
- references/api-reference.md: real API documentation with method signatures
- LICENSE: MIT license for all skill folders

skills/performing-timeline-reconstruction-with-plaso/references/api-reference.md

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+# API Reference: Timeline Reconstruction with Plaso Agent
+
+## Overview
+
+Wraps Plaso (log2timeline/psort) via subprocess for forensic super-timeline generation, filtering, export, and automated CSV analysis for activity spikes and source distribution.
+
+## Dependencies
+
+| Package | Version | Purpose |
+|---------|---------|---------|
+| csv | stdlib | Timeline CSV parsing |
+| subprocess | stdlib | Plaso tool execution |
+
+## External Tools Required
+
+| Tool | Purpose |
+|------|---------|
+| log2timeline.py | Forensic timeline generation from disk images |
+| psort.py | Timeline filtering, sorting, and export |
+
+## Core Functions
+
+### `run_log2timeline(image_path, storage_file, parsers, filter_file)`
+Executes log2timeline.py to parse a disk image into a Plaso storage file.
+- **Parameters**: `image_path` (str), `storage_file` (str), `parsers` (str, optional), `filter_file` (str, optional)
+- **Timeout**: 7200 seconds (2 hours)
+- **Returns**: `dict` with command, returncode, stdout, stderr
+
+### `run_psort_export(storage_file, output_file, output_format, date_filter)`
+Exports timeline from Plaso storage to CSV, JSONL, or dynamic format.
+- **Formats**: `l2tcsv`, `json_line`, `dynamic`
+- **Returns**: `dict` with command, returncode, output_file
+
+### `create_filter_file(filter_path, paths)`
+Generates a Plaso filter file targeting key forensic artifacts.
+- **Default paths**: winevt, Prefetch, NTUSER.DAT, Chrome, Firefox, MFT, USN Journal, registry
+
+### `analyze_timeline_csv(csv_path, max_rows)`
+Statistical analysis of exported timeline: source distribution and hourly activity spikes (>3x average).
+- **Returns**: `dict` with `total_events`, `source_counts`, `spike_hours`, `avg_events_per_hour`
+
+### `generate_incident_window(storage_file, output_dir, start_date, end_date)`
+Exports events within a specific date range for focused analysis.
+
+### `full_pipeline(image_path, output_dir, parsers, start_date, end_date)`
+End-to-end pipeline: log2timeline -> psort export -> CSV analysis -> incident window -> JSONL export.
+
+## Default Parsers
+
+```
+winevtx, prefetch, mft, usnjrnl, lnk, recycle_bin,
+chrome_history, firefox_history, winreg
+```
+
+## Usage
+
+```bash
+python agent.py /cases/evidence.dd /cases/timeline/ "2024-01-15 00:00:00" "2024-01-20 23:59:59"
+```
+
+## Output Files
+
+| File | Format | Purpose |
+|------|--------|---------|
+| evidence.plaso | SQLite | Plaso intermediate storage |
+| full_timeline.csv | L2T CSV | Complete super-timeline |
+| incident_window.csv | L2T CSV | Filtered incident period |
+| timeline.jsonl | JSON Lines | SIEM/Timesketch import |