Spillwave Solutions
Official@spillwavesolutions · United States of America
Hardcore engineers engaged in prolific AI and Agentic activities
Agent Skills by Spillwave Solutions
Showing 53 vetted skills indexed across 31 GitHub repositories.
mastering-langgraph
Build stateful AI agents and workflows with LangGraph in Python.
parallel-worktrees
Coordinate multiple Claude Code agents across isolated git worktrees for parallel development.
configuring-codebase-wizard
Install hooks, configure storage, and set permissions for Codebase Wizard across runtimes.
explaining-codebase
Explain codebase components with anchored code blocks and plain-English descriptions.
exporting-conversation
Convert wizard session JSON into structured Markdown documentation files.
gemini
Pipe input content to the Gemini CLI for headless AI tasks and file outputs.
image-gen
Generate cover images and in-article diagrams with the imagen CLI.
release-rulez
Automate RuleZ releases from Cargo.toml versioning to GitHub Actions monitoring.
AWS CDK Skill
Provide AWS CDK development guidance with TypeScript and best practices.
mastering-gcloud-commands
Identify valid Skill Units and extract resource details into a YAML metadata profile.
grading-claude-agents-md
Grade CLAUDE.md and AGENTS.md files against a four-pillar rubric.
Local Install Skill
Build and install Agent Brain CLI and server locally with Python 3.11, Poetry, and uv.
using-agent-brain
Search indexed documents across BM25, vector, hybrid, and graph modes.
configuring-agent-brain
Install and configure Agent Brain for document search with pluggable providers.
memory-llm
Configure LLM providers for agent-memory summarization via interactive wizard.
memory-setup
Automate agent-memory installation setup, configuration, and troubleshooting across platforms.
memory-storage
Configure agent-memory storage paths, retention policies, GDPR mode, and performance tuning.
memory-agents
Configures multi-agent memory settings through an interactive wizard.
memory-query
Query past conversations with tiered retrieval and explainable results.
bm25-search
Search exact terms and phrases in the agent-memory index with BM25 scoring.
retrieval-policy
Automates retrieval policy decisions with tier detection, intent classification, and layer routing.
vector-search
Perform semantic vector search over agent-memory with hybrid BM25+vector fusion.
topic-graph
Construct and query a time-decayed topic graph from agent-memory conversations.
mastering-aws-cdk
Build and debug AWS CDK v2 infrastructure in TypeScript.
Frequently Asked Questions About Spillwave Solutions
FAQPage SchemaWhat specific technical tasks can I perform with these capabilities?▼
You can generate architectural diagrams from code, synchronize documentation across Confluence and Notion, manage AWS infrastructure via TypeScript, and implement hybrid search systems using BM25 and vector embeddings for document retrieval.
Which engineering personas benefit most from these technical modules?▼
These modules are designed for platform engineers, technical architects, and documentation specialists who require structured methods for managing codebase memory, infrastructure deployments, and cross-platform knowledge synchronization.
What are the primary prerequisites for deploying these system components?▼
Deployment requires a standard environment supporting TypeScript 5.9+, Python 3.11, and Poetry. Additionally, users must have active credentials for target platforms like AWS, GitHub, Confluence, or Notion to enable the respective integration modules.