pentest-ai-agents
Provides Claude Code subagents for offensive security research and penetration testing planning. Covers reconnaissance analysis, exploit research, detection engineering, and security reporting.
Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Provides Claude Code subagents for offensive security research and penetration testing planning. Covers reconnaissance analysis, exploit research, detection engineering, and security reporting.
Guides prompts for subagents and other LLM interactions, including commands, hooks, and agent skills. Supports prompt optimization, improved model outputs, and production template design.
Guides Qdrant server and SDK upgrades, including rolling upgrades, version compatibility, and client/server sequencing. Covers pre-upgrade checks and investigation of behavior changes after upgrades.
Design interfaces for use across locales. Address text expansion, right-to-left mirroring, and locale-specific formats across languages and cultural contexts.
Use the relationship between simultaneous choices and decision time to guide interface design. Apply it when a screen presents too many options at once.
Apply the Von Restorff Effect to make a single element stand out and be remembered. Focuses on dominant emphasis for one action rather than the overall ordering of visual attention.
Audits design inconsistencies that have accumulated across a product over time. Produces an inventory and prioritization of design debt.
Supports Factory connection and login, queue summaries, project and work-item inspection, thread history, memory, metrics, and health checks. Covers decisions, attention, supervisor sessions, and authorized autonomous or interactive operations across hosted, local, remote, and self-hosted servers.
Apply the skill's Miller's Law framing to chunk information into groups of about four. Use it when organizing fields, menu items, or steps around working-memory limits.
Controls texture appearance and addresses texture memory issues in React Three Fiber. Covers color spaces, UV channels, sampling, video textures, and render targets.
Guides skill creation and modification, including initialization, scaffolding, and validation. Explains skill structure and design patterns for extending agent capabilities with knowledge, workflows, and tools.
Uses Tigris Agent Kit for isolated dataset forks, per-agent buckets with TTL, and checkpoint-based snapshot and restore. Supports event-driven pipeline coordination through bucket webhooks.
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name