shakudo
Official@shakudo-io
An end-to-end MLOps platform
Agent Skills by shakudo
Showing 46 vetted skills indexed across 1 GitHub repositories.
Shakudo-iographiti-memory
Search and record institutional knowledge in Graphiti memory graphs.
Shakudo-iodeepgram-stt
Convert spoken language into searchable text via the Nova-3 model.
Shakudo-ioiac-terraform
Deploy Terraform and Terragrunt workflows for cloud infrastructure provisioning and management.
Shakudo-ioai-bdr
Automate outbound cold calls with ElevenLabs Conversational AI and retrieve transcripts.
Shakudo-iomattermost-notify
Send Mattermost direct messages when tasks complete, fail, or need attention.
Shakudo-ioshakudo-microservice
Automate deployment, restart, scaling, and monitoring of Shakudo microservices.
Shakudo-iogit-workflow
Enforce Git branch, commit, and pull request conventions for business-automation projects.
Shakudo-iotwilio-sms
Automate Twilio REST API workflows for SMS, voice calls, and WhatsApp messaging.
Shakudo-iogoogle-oauth
Run a local Google OAuth 2.0 flow with token persistence to .env.
Shakudo-iorecruit-workflow
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Shakudo-ioplaywright-skill
Automate browser testing with Playwright against local dev servers.
Shakudo-iohubspot
Automates HubSpot CRM REST API CRUD, search, and association operations for core objects.
Shakudo-ioelevenlabs-voice
Generate speech and sound effects via the ElevenLabs API.
Shakudo-iogitops-workflows
Orchestrate GitOps deployment automation with ArgoCD and Flux in Kubernetes.
Shakudo-iozellij
Automate terminal session management with panes, tabs, and layouts.
Shakudo-iomailgun-email
Send transactional emails and manage templates via the Mailgun REST API.
Shakudo-iodremio-analytics
Query Dremio to retrieve CRM, billing, and business analytics data.
Shakudo-ioproject-memory
Create and maintain structured project memory files in docs/project_notes.
Shakudo-iotmux
Register and manage tmux sessions with a registry-backed workflow.
Shakudo-ioneo4j-graph-rag
Query a Neo4j knowledge graph for semantic retrieval across transcripts, threads, and emails.
Shakudo-iopagerduty-ops
Trigger, acknowledge, and resolve PagerDuty incidents via REST and Events APIs.
Shakudo-iomonitoring-observability
Map SLIs to Four Golden Signals and identify monitoring coverage gaps.
Shakudo-iocontext-engineering-collection
Identify, categorize, and deploy Agent Skills for context engineering in AI agents.
Shakudo-ioci-cd
Design CI/CD pipelines across GitHub Actions, GitLab CI, and other platforms.
Frequently Asked Questions About shakudo
FAQPage SchemaWhat specific tasks can engineers perform using Shakudo?▼
Engineers can manage complex agent memory systems, perform semantic retrieval via Neo4j, optimize context windows through compaction, and orchestrate multi-agent handoffs. Additionally, the platform supports infrastructure provisioning, Kubernetes incident remediation, and the creation of fine-tuning datasets from existing documentation.
Which technical personas benefit most from these capabilities?▼
The platform is designed for MLOps engineers, AI systems architects, and backend developers focused on building reliable, production-ready agentic systems. It provides the necessary primitives for those responsible for maintaining long-running agent sessions, monitoring model reasoning traces, and ensuring robust infrastructure deployment.
What are the core prerequisites for deploying these agentic patterns?▼
Users require a configured environment capable of supporting containerized workloads, access to vector or graph databases like Neo4j for memory persistence, and established CI/CD pipelines. Familiarity with structured data formats like JSONL and RDF is recommended for advanced context and mental state modeling.