crystallize

Converts finished Falcon MCP investigations into standalone Python scripts that render HTML dashboards.

3|1|Updated Sep 1, 2026
One-click install
npx skills add https://github.com/kyle9021/fal_con_2026_AI-Powered-Cloud-Security-Ops-Falcon-Mcp --skill crystallize-kyle9021
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: crystallize
Source: https://github.com/kyle9021/fal_con_2026_AI-Powered-Cloud-Security-Ops-Falcon-Mcp/tree/main/.claude/skills/crystallize
Command: npx skills add https://github.com/kyle9021/fal_con_2026_AI-Powered-Cloud-Security-Ops-Falcon-Mcp --skill crystallize-kyle9021

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Re-running a completed security investigation through an AI model every day wastes tokens on a discovery already made. This Skill turns a finished CrowdStrike Falcon MCP investigation into a deterministic, GET-only Python script that calls the Falcon REST API directly and renders a self-contained HTML dashboard, so the same question can be answered on a schedule at zero token cost. ## Core Features & Use Cases - MCP-to-REST translation: Maps falcon_* MCP tools to verified Falcon REST endpoints, transferring FQL filters verbatim and unlocking multi-facet queries the MCP layer hides. - Deterministic, auditable output: Generates scripts with token pagination, denial-aware gap reporting, exit codes for CI gating, and full query provenance recorded in the dashboard. - Cross-cloud resolution patterns: Handles AWS, Azure, and GCP instance-to-image resolution, including VMSS parents, ARM paths, and CSPM two-step entity lookups. - Use Case: After an interactive investigation reveals which vulnerable base images drive the most downstream exposure, crystallize it into a cron-scheduled script that regenerates the ranked dashboard every morning without any model involvement. ## Quick Start Ask the AI to crystallize the investigation we just finished into a repeatable scheduled script with a dashboard.

Frequently Asked Questions about crystallize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate a Falcon MCP investigation without a model?▼

Crystallize it into a standalone Python script that calls the Falcon REST API directly using the repo's GET-only falcon_api.py client. The script preserves the investigation's ranking logic in code and renders an HTML dashboard, running on cron or CI with zero token cost.

How do I translate Falcon MCP tools to REST API endpoints?▼

Each falcon_* MCP tool wraps one or two REST calls, and FQL filter strings transfer verbatim. Verified mappings are provided for Spotlight vulnerabilities, containers, detections, hosts, and CSPM assets; for others, grep FalconPy's machine-readable endpoint spec rather than guessing paths.

When should I not crystallize an investigation into a script?▼

Do not crystallize when each run needs fresh judgment about what to chase next, or when a later question's shape depends on earlier answers in ways you cannot express as an if statement. Those investigations should stay interactive on the MCP path.

Does the generated script need the MCP server or extra Python packages?▼

No. The generated script imports only the repo's stdlib-only falcon_api.py and falcon_report.py modules and runs on Python 3.9+. It does not use the MCP server, FalconPy, or any pip-installed dependency at runtime.

Why does my crystallized dashboard show unavailable instead of zero?▼

The script treats API denials (401/403/404) as unknown rather than zero, passing None to the metric and recording a gap explaining which signal was unavailable. This prevents a missing API scope from being reported as a false all-clear.

Can the crystallized script write to my Falcon tenant?▼

No. The script uses a deliberately GET-only client with no code path that can modify tenant state. Any action-taking automation is a separate, explicitly reviewed piece of work, not a side effect of report generation.