Skill UI

Provides a workflow that publishes content while automatically summarizing key points, keeping final copy release-ready and highlighting insights for stakeholders and follow-up actions.

This tool allows users to explicitly save critical, project-specific facts, conventions, or debugging insights to a dedicated auto-memory file. Use it when the knowledge is too important or specialized to rely on the AI's automatic context capture. It ensures persistent recall of architectural decisions, tool gotchas, or team preferences across multiple sessions and projects.

This skill provides a comprehensive guide for creating production-quality custom Semgrep rules. It teaches best practices for detecting security vulnerabilities, enforcing robust coding standards, and identifying specific bug patterns. By emphasizing a test-first approach and utilizing advanced techniques like taint mode, users can write highly accurate static analysis rules that drastically reduce false positives.

This skill provides a robust and safe mechanism for updating SpecKit templates and configurations from GitHub. It is designed to automatically apply the latest changes while meticulously preserving any existing project customizations, ensuring a non-disruptive workflow. It features a conversational, two-step approval process, guiding the user through the update process, reporting conflicts, and handling fresh installations gracefully. Ideal for developers needing reliable, version-controlled updates to their SpecKit environment.

This skill guides users in systematically organizing and documenting a year's worth of past projects into the specific SRED format. It processes scattered evidence—including GitHub PRs, Notion documents, and Linear tickets—to evaluate project suitability, generate comprehensive descriptions, and create structured, standardized reports within Notion. Ideal for formal academic submissions or professional portfolio creation.

This skill aggregates a user's entire year's work—including GitHub PRs, Notion documents, and Linear tickets—into a single, structured Notion document. It automatically groups these artifacts by project, providing a comprehensive and organized summary ideal for professional reviews or annual performance documentation (e.g., SRED preparation).

This methodology provides a structured framework for stress-testing critical business assumptions before they fail in the market. Learn to systematically identify, challenge, and model the downside risk associated with market size, revenue projections, competitive moats, and customer behavior. It moves beyond optimism to achieve crucial business calibration.

This tool systematically audits a project's dependencies to identify potential supply chain security risks. It evaluates critical factors such as maintenance status, contributor count, popularity, and the presence of high-risk features. It is ideal for pre-security audits, assessing the overall attack surface, and mitigating risks before deployment.

Coordinates discovery, matching, and workflow orchestration across agent ecosystems, automatically scanning SKILL.md, ranking relevant skills, and executing multi-step plans for complex requests.

Enables an OpenClaw agent to place managed outbound phone calls for alerts, briefings, reminders, and urgent notifications without Twilio, combining REST-triggered dialing with transcription and TTS so conversations feel like chat.

This agent ensures seamless continuity across multiple work sessions. It automatically captures, compresses, and stores critical project information—including summarized discussions, architectural decisions, pending tasks, modified files, and technical discoveries. When a new session starts, it loads a comprehensive briefing, allowing users to quickly resume work without losing track of the project's current state.

A framework for building production-ready, low-latency, multimodal AI agents. It allows developers to orchestrate complex pipelines that seamlessly handle real-time audio, video, and text data. Key capabilities include integrating multiple AI services (LLMs, STT, TTS), managing conversation context, and enabling tool use and function calling for advanced, interactive AI applications.