Agent Skills Hub

git-commit

Execute git commits with conventional commit message analysis, intelligent file staging, and automated semantic message generation based on code diffs.

landing-page-angle-tester

Generate diverse landing page narrative angles, define target audiences, and specify required evidence for conversion-focused marketing workflows.

receiving-code-review

Rigorous, non-performative code review reception for AI agents, prioritizing technical verification and YAGNI over passive agreement.

langchain-chat-models

A unified interface for integrating and managing LLM chat providers like OpenAI, Anthropic, Google, Azure, and Bedrock within LangChain applications.

commit-messages

Generate consistent, Conventional Commits-compliant messages directly from your staged git diffs.

context-degradation

Diagnose, isolate, and mitigate LLM context failures like lost-in-middle, poisoning, distraction, and context clash to improve agent reliability.

customer-feedback-analyzer

A framework for collecting, analyzing, and prioritizing user feedback across multiple channels to drive product strategy and feature development.

internal-comms

Standardize your internal communications using company-specific guidelines and templates for reports, newsletters, and project updates.

tikhub-api-helper

Search and query TikHub social media APIs for TikTok, Douyin, Xiaohongshu, Instagram, YouTube, and more to fetch cross-platform data.

ring:writing-skills

A framework for applying Test-Driven Development to process documentation, ensuring agent reliability by using pressure scenarios to identify and patch rationalization loopholes.

context-management

Proactive context window management for AI agents via intelligent token monitoring, snapshot creation, and selective state rehydration to maintain continuity during long sessions.

explore

Meta-skill for structured, multi-depth codebase exploration including architectural analysis, fast structural overviews, and deep-dive documentation workflows.