Agent Skills Hub

wormhole

Shared memory and collaboration layer for AI coding agents to track actions, manage sessions, detect conflicts, and preserve project context across tools.

repo-sync

Automated repository synchronization for multi-repo ecosystems, featuring intelligent failure diagnosis, auto-repair for Git state issues, and integrated ecosystem health checks.

paper-figure

Generate publication-quality figures, charts, and LaTeX tables from experiment data for academic papers.

review-collector

Automated compliance validation tool for collector bot packages using 8 specialized parallel agents.

swe-cli-skills

Expert CLI guides for AI agents, featuring senior engineer workflows, safety guardrails, and operational patterns for cloud, IaC, containers, databases, and dev tools.

agent-architecture

Implement production-grade AI agents with LangGraph, tool-calling guardrails, SSE streaming, and episodic memory. Includes anti-patterns, fix pairs, and stateful architecture patterns.

requesting-code-review

Enforces code quality by dispatching a dedicated subagent to review work against project plans, requirements, and git commit history before tasks are completed or merged.

session-logs

Search, analyze, and audit GeminiClaw session logs and memory. Use to investigate past interactions, track token usage, debug tool calls, and monitor agent performance.

git.pr.create

Automate pull request creation for Carbon ACX with comprehensive summaries, structured test plans, and standardized formatting using the GitHub CLI.

inno-prepare-resources

Automates research resource preparation by loading instances, searching GitHub for codebases, building dataset descriptions, and downloading arXiv papers.

MigrationBox-v4

MIKE-FIRST v6.0: An enterprise multi-cloud resilience platform for compliance auditing, security intelligence, and zero-downtime cloud migration.

recursive-decomposition

Handles large-scale tasks by automatically breaking them down into manageable, recursive sub-tasks to overcome context window limits and improve reasoning accuracy on large codebases and document sets.