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Found 821 Skills
Architecture patterns and best practices for giving AI agents email capabilities. Use when designing how agents send, receive, and manage email conversations, building two-way communication loops, implementing human-in-the-loop approval with drafts, choosing between WebSockets and webhooks, setting up multi-agent email topologies, handling OTP and verification flows, or securing agent email against prompt injection.
Draft or update requirement documents under `codestable/requirements/` for the project — use **user stories + plain language** to describe a capability's "reason for existence, solution approach, and boundaries", so non-technical readers can quickly understand the highlights of the system. Layered with architecture: requirement is the "problem space" (why this capability is needed), while architecture is the "solution space" (what structure is used to implement it). Two modes: new (draft a new requirement doc from scratch), update (refresh an existing doc based on new materials or implementation changes). Single-target rule — only modify one document at a time. Trigger scenarios: the user says "fill in a requirement doc", "write down the requirements for this capability", "update the requirements directory", or during the feature-design phase, it is found that there is no corresponding requirement for the capability to be implemented this time.
Automated data quality and transformation capabilities for Dataform/dbt/BigQuery pipelines. Processes data sourced from BigQuery or Cloud Storage (GCS), applying best practices for data ingestion, movement, schema mapping, and comprehensive data cleaning.
Deep dive into LookML includes, refinements (layering), and project structure best practices. Essential for mastering Looker's object-oriented capabilities.
Create Xmind mind maps with generated topic images via a contact-sheet workflow. Requires an image generation capability (built-in for Codex / Gemini CLI, or an external image API). Use for illustrated maps; for text-only maps, use xmind-file.
Skill Evolver (Taotie) — Strengthen the target skill by "devouring" and analyzing the advantages of other skills. This skill must be triggered when users intend to: integrate two skills, optimize one skill with another, compare and analyze the pros and cons of two skills, extract the strengths of one skill into another, or express intentions like "feed X to Y", "use X to optimize Y", "integrate these two skills", "devour this skill", "skill evolution", "skill upgrade", "merge skills", etc. Even if users don't explicitly mention "Taotie", this skill should be used as long as it involves capability transfer, comparative analysis, or advantage extraction between two skills.
Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK/IAM/quota error diagnosis, version management, rollback, and canary deployments. Triggers on: "deploy my agent", "agentcore deploy", "deploy failed", "CDK error", "rollback", "canary deploy", "pin version", "redeploy", "deploy stuck". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.
Keep gbrain current with this repo's code and refresh agent search guidance in CLAUDE.md. Wraps the gstack-gbrain-sync orchestrator with state probing, native code-surface registration, capability checks, and a verdict block. Re-runnable, idempotent. Use when: "sync gbrain", "refresh gbrain", "re-index this repo", "gbrain search isn't finding things". (gstack)
Plan and run backups, set recovery objectives, and run disaster recovery drills. Use this skill when defining RPO/RTO targets, designing backup architecture, deciding what to back up and how often, planning for full-region or platform outages, or running a restoration drill. Triggers on backup, restore, RPO, RTO, disaster recovery, DR, business continuity, what if the database is gone, what if our hosting goes down, recovery drill, ransomware planning. Also triggers when an incident reveals a gap in restoration capability.
Designing in-product tours, tooltips, and contextual help that teach product capabilities without becoming friction. Trigger logic, tour architecture, contextual placement, completion tracking. Honest about tooltip-spam (visual noise that users develop blindness to), one-and-done (help invisible at the moment of need), and contextual-when-needed (surfaces help at the moment friction occurs) patterns. Triggers on product tour, in-product tooltip, contextual help, walkthrough, feature tour, hint system, in-app guidance, tour platform. Also triggers when feature adoption is low, when users miss key product capabilities, or when an in-product help system is being scoped for the first time.
Discover and cache all installed ComfyUI models, custom nodes, and system capabilities. Works online (API queries) and offline (directory scanning). Use before generating workflows to verify available resources.
Specification and SDK for creating Agent Skills - a standard format for giving AI agents new capabilities through discoverable instruction bundles