LLM Mart Basic

Use this skill to review Databricks data protection and privacy design for regulatory alignment and least-privilege enforcement: row filters and column masks, ABAC policies, data classification, deletion and GDPR erasure mechanics, Delta Sharing egress, residency and Geo constrai

Use this skill to design and verify data quality expectations, table constraints, Lakehouse Monitoring, freshness detection, event-log interrogation, quality SLAs, and downstream quality signaling for Lakeflow pipelines. Reads pipeline source, table schema, expectations, monitor

Use this skill to review a Declarative Automation Bundle configuration, authentication setup, and deployment flow against production readiness criteria: bundle structure, deployment modes, run-as identity boundaries, variable resolution timing, OAuth and environment-variable auth

Use this skill to statically review Databricks cost and cost-attribution: system.billing.usage and system.billing.list_prices for correct joins, custom-tag-based attribution with coverage-confidence reporting, DBU uptime charging semantics, serverless versus classic cost comparis

Use this skill to review generative-AI agent design on Databricks: Mosaic AI Agent Framework and ResponsesAgent interface, Databricks AI Search index variant and sync-mode choice, retrieval and context engineering, MCP server category and trust boundaries, external model-provider

Use this skill to review generative-AI evaluation, tracing, and observability design on Databricks: MLflow Tracing instrumentation and span design, trace storage and governance, `mlflow.genai.evaluate()` harness design, the judge-versus-scorer distinction, built-in judge selectio

Use this skill to review Databricks identity and network security design for proper admin separation, SCIM/federation configuration, credential hygiene, and network boundary enforcement: admin roles, service-principal posture, OAuth vs PAT, token lifecycle, IP access lists, serve

Use this skill to design Lakeflow Spark Declarative Pipelines: medallion layering, Lakeflow Jobs orchestration and task dependencies, Delta table layout (liquid clustering, deletion vectors, Predictive Optimization), Auto Loader ingestion, schema evolution and `_rescued_data`, ma

Review and guide Databricks Lakehouse engineering on Azure: medallion architecture (bronze/silver/gold), Delta Lake pipelines, ADLS Gen2 access via Unity Catalog external locations and storage credentials, Access Connector managed identity, cluster access mode enforcement, AKV-ba

Mutating-runtime live guard for Unity Catalog privilege management on Azure Databricks. Executes exactly ONE GRANT or REVOKE of a single privilege on a single Unity Catalog securable (schema, table, or volume) to a single principal — with explicit written human approval, dry-run

Use this skill to classify an incoming Databricks task and route it to the narrowest owning specialist on the Databricks board. Classifies on intent, business context, artifact type, blast radius, required evidence, implied runtime authority, and specialist ownership; emits a sin

Use this skill to review machine-learning model lifecycle on Databricks: MLflow 3 with Unity Catalog as default registry, alias-based promotion and champion/challenger patterns, feature-store design with point-in-time correctness, Model Serving endpoint configuration and traffic

Use this skill to review Databricks account and workspace topology for scalability and Well-Architected alignment: metastore-per-region constraint, workspace segmentation ratios, serverless vs classic placement, catalog organisation, cross-region and cross-organisation access pat

Use this skill to diagnose and design platform reliability using system-table evidence, job and pipeline execution review, cluster policies, instance pools, quota headroom, and disaster-recovery posture: job timeouts and retries, run-history retention, managed DR design, incident

Use this skill to statically review SQL warehouse and query performance: warehouse type and sizing for concurrency, Photon and Predictive I/O applicability, three-tier caching semantics and when a cached result is misleading, query-profile reading for skew and spill, data layout

Use this skill to verify Structured Streaming query correctness and recovery: state-schema immutability, checkpoint compatibility across restarts, watermark semantics, trigger selection (AvailableNow, Once, ProcessingTime), exactly-once vs at-least-once sinks, foreachBatch idempo

Use this skill to review Unity Catalog governance design for privilege correctness, ownership clarity, and least-privilege enforcement: three-level namespace design, GRANT inheritance, ownership, workspace-catalog binding, governed tags, storage credentials, and audit completenes

Review Databricks Unity Catalog governance on Azure: three-level namespace design, GRANT privilege model, identity federation with Microsoft Entra ID, service principal posture, workspace-catalog binding, account/workspace/metastore admin separation, audit via system tables, and

Use this skill to decide whether a claimed Databricks business outcome is measurable, and only then to size it. Builds a value case from a named pain, a named executive owner, a pre-change baseline, a leading metric, a lagging business KPI, the required data, explicit attribution

Use this skill when reviewing a .NET Aspire AppHost or service-defaults project for cloud-native readiness — health checks on declared service dependencies, service dependency wiring, resiliency policies on outbound calls, configuration and secret hygiene, configuration drift bet

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

One-line reliability verdict (OK / DEGRADED / FAILING) for Claude Code usage

Print a quick SLO snapshot — completion rate, tool success rate, and error rate

Generate an evidence-backed CCAM executive, cost, reliability, or workflow report.

List live and persisted CCAM-launched Claude Code and Codex runs

Search Agent Monitor sessions by cwd, model, or status and print the top matches.

List the N most recent Claude Code sessions from the Agent Monitor.

Summarize one Agent Monitor session by id — header plus a concise transcript recap.

Print the orchestration DAG edges (parent→child subagents) for a session.

List recent Workflow-tool fleet runs with status and agent counts.

Summarize the workflow intelligence for a session — stats, complexity, and top patterns.

Run broadcast on a distilled Raw — update related existing pages conversationally

Distill raw session records into refined Notes and Projects

Save knowledge to the cortex vault (Notes or Projects) and update index

Initialize cortex vault — set up config, vault structure, and rebuild index

Manually search the cortex vault (Notes, Projects, Raw) for existing notes

Create, resume, or clear a session hand-off baton (one per work line)

Command → Agent → Skill orchestration for end-to-end feature development.

Command → Agent → Skill orchestration for investigating and fixing bugs.

Brief the CEO: coordinate with peer CTO and CAIO executives and start or resume a founder project across 9 departments and 64 skills

Configure an optional active team profile in three short questions

Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-model, multi-channel. Lightwei…

Open-source AI browser agent for web automation: a web browsing agent and computer-use agent in plain English. Browser MCP for Claude Code and Gemini CLI.

Agent-native trading terminal built on DeepSeek Harness. Crypto, US, CN and HK in one three-column GUI, 19+ hot-swappable connectors, dry-run by default with hu…

Open-source desktop and web coding agent with a first-party host and harness, durable sessions, model connections, streaming chat, and workspace tools.

OrcaReplay — Time travel for AI agents. Record, replay, fork, and debug any agent run with any model. Built by the OrcaRouter.ai team.

A complete toolkit for connecting R and LLMs

OpenSRE — the memory-first AI SRE. Self-hosted incident investigation with episodic memory, knowledge graph, web console, Slack & Teams. opensre.in

A desktop AI coding assistant that works with your local projects. Ally helps you understand code, edit files, search a workspace, manage tasks, and complete de…

【在线免费使用】 简单快速将SQL或DBML转换为美观的ER图（支持 Agent Skill）/ The best SQL to ER Diagram converter (Support Agent Skill).

Operation-bound protection for autonomous AI agents: contain and verify operations before committing changes, understand intent and risk across long-running wor…

Local-first AI coding agent desktop: Electron + Rust host core + pi Agent Harness + user-installable plugins

Local-only Go static analysis engine with a built-in MCP server. Gives AI coding agents deterministic structural awareness: call graphs, impact analysis, symbol…

Self-hosted AI agent workspace with tool calling, MCP, multi-model routing, sandboxed execution, multi-agent workflows, and LLM-authored 3D character animation…

Automated TDD enforcement for Claude Code

High-performance platform for building websites, e-commerce, and web applications—with Native AI, JavaScript development, and a marketplace for portable sites a…

Autonomous AI-agent orchestration engine for job discovery with decision traces, tool adapters, and production-grade run control.

Token efficient Claude Code full Python rebuild. AI Coding Agent in 310K LoC Python.

OPC — One Person Company. A full team in a single Claude Code skill. Adaptive agent orchestrator with 21 built-in roles, 6 flow templates, and adversarial quali…

Open-source, secure environment with real-world tools for enterprise-grade agents.

MCP server for AI-powered GitHub project management — agent orchestration, PRD-to-issues pipeline, sprint planning, and multi-agent swarm coordination