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Found 58 Skills
Use when starting work on any project to produce or update living documentation (TechStack.md, ProjectStructure.md) that bootstraps context for any AI agent session. Run before any feature work, or periodically to keep docs current.
Use when implementing features, writing fullstack code, shipping UI + API + DB changes, or any hands-on engineering work in TypeScript, Python, React, Next.js, FastAPI, or SQL
Bootstraps a new AI-assisted project through a structured 4-phase conversation, then generates PROJECT.md, JOURNAL.md, .gitignore, and tmp/README.md. Also searches skills.sh and installs relevant skills for the approved tech stack. Use when starting a new project from scratch or when no PROJECT.md exists in the current directory. Do NOT trigger if PROJECT.md already exists — redirect to /project-sync instead. Invoke with /project-init — never auto-trigger.
OSINT-based technology stack identification. Discovers company tech stacks using passive reconnaissance across 17 intelligence domains. Given a company name (and optional domain hint), infers frontend, backend, infrastructure, and security technologies using publicly available signals.
Project scaffolding templates for new applications. Use when creating new projects from scratch. Contains 12 templates for various tech stacks.
CVE vulnerability testing coordinator that identifies technology stacks, researches known vulnerabilities, and tests applications for exploitable CVEs using public exploits and proof-of-concept code.
UI/UX Design Intelligence, a must-use resource when conducting page design work
Designs system architecture and selects technology stack based on vision analysis. Use after vision analysis for technical decisions. Triggers on: design architecture, select tech stack, choose framework.
Generate implementable architecture solutions based on business requirements and tech stacks, providing structured suggestions and tech stack selection optimization through a four-step process (information collection, requirement sorting, iterative improvement, solution output)
Analyze project briefs to resolve architectural ambiguity before tech stack selection. Determines greenfield vs brownfield, platform constraints, integration requirements, scale expectations, and team context. Produces architecture-context.json for downstream skills.