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-soc-tabletop-exercise/references/api-reference.md

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+# API Reference: SOC Tabletop Exercise Agent
+
+## Overview
+
+Manages SOC tabletop exercise lifecycle: scenario generation from templates, participant tracking, inject delivery, response scoring, and after-action report generation.
+
+## Dependencies
+
+| Package | Version | Purpose |
+|---------|---------|---------|
+| json | stdlib | Report serialization |
+| datetime | stdlib | Exercise scheduling and IDs |
+
+## Core Functions
+
+### `create_exercise(scenario_type, participants, duration_hours=3)`
+Creates a structured tabletop exercise from a scenario template.
+- **Parameters**: `scenario_type` (str) - one of `ransomware`, `data_breach`, `supply_chain`; `participants` (list[dict]) - role/count pairs
+- **Returns**: `dict` - full exercise object with phases and objectives
+
+### `score_response(category, score)`
+Scores participant response in a specific evaluation category.
+- **Parameters**: `category` (str) - one of `detection_and_triage`, `containment_decision`, `communication`, `business_continuity`; `score` (int) - 0-100
+- **Returns**: `dict` - category, score, rating, weight
+
+### `calculate_overall_score(scores)`
+Computes weighted average across all scored categories.
+- **Parameters**: `scores` (list[dict]) - output from `score_response`
+- **Returns**: `float` - overall score
+
+### `generate_after_action_report(exercise, scores, gaps, strengths)`
+Produces the formal after-action report document.
+- **Parameters**: `exercise` (dict), `scores` (list), `gaps` (list[dict]), `strengths` (list[str])
+- **Returns**: `dict` - AAR with scores, findings, and next exercise date
+
+## Scenario Templates
+
+| Template | Phases | Focus Areas |
+|----------|--------|-------------|
+| `ransomware` | 6 injects | Detection, containment, ransom decision, recovery |
+| `data_breach` | 4 injects | DLP, insider threat, PII notification |
+| `supply_chain` | 4 injects | Vendor compromise, lateral movement, credential reset |
+
+## Scoring Criteria
+
+| Category | Weight | Rating Thresholds |
+|----------|--------|-------------------|
+| detection_and_triage | 25% | >=85 Excellent, >=70 Good, >=55 Adequate |
+| containment_decision | 25% | >=85 Excellent, >=70 Good, >=55 Adequate |
+| communication | 25% | >=85 Excellent, >=70 Good, >=55 Adequate |
+| business_continuity | 25% | >=85 Excellent, >=70 Good, >=55 Adequate |
+
+## Output Schema
+
+```json
+{
+  "exercise_id": "TTX-2026-Q1",
+  "overall_score": "72/100 (Adequate)",
+  "scores": {"detection_and_triage": "85/100 (Excellent)"},
+  "gaps": [{"finding": "...", "risk": "High", "owner": "SOC Manager"}],
+  "strengths": ["Ransomware indicators correctly identified"]
+}
+```