LLM Mart Basic

Use this skill when a Salesforce matter must be assigned a standardized matter type, risk tier, or escalation gate before routing or handoff. Defines all matter types (org-config, automation, code, integration, security/IAM, data, sales/CPQ, service/SLA, experience-cloud, marketi

Use this skill when a Salesforce matter must be classified and routed to the right specialist agent, when a matter crosses multiple Salesforce domains and needs parallel review, or when specialist agents disagree and the conflict must be resolved. It defines routing rules per mat

Use this skill to statically review AI/BI Genie agent and dashboard design: agent scoping (30-table limit), instructions and trusted assets, metric-view correctness, dashboard limits and rendering, benchmark design and honest accuracy reading, and the critical 'Individual data' v

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

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.

Cache-miss / compaction protection gate (disabled by default)

Reference the supported Claude Code command, skill, plugin, and hook surfaces

Clear all session-level pattern blocks and allows

Emergency stop - immediately halt all autonomous operations

Find existing files only - no new file creation (short for /ar:find)

Find existing files only - prevents new file creation (strictest mode)

Git commit requirements - the 17-step process, short for /ar:commit

Use gemini CLI for any combination of: superior vision for analysis of images, diagrams, screenshots, PDFs, documents, video, and audio; code review with detailed citations and cross-referencing patterns; Google search; and multi-model workflows; all for planning, feedback, and getting unstuck.

Clear all global pattern blocks and allows

Block a command pattern globally (persists across sessions)

Allow a blocked pattern globally (persists across sessions)

Show active global pattern blocks and allows

Start autorun - autonomous task execution (short for /ar:run)

Start autoproc - procedural autonomous workflow (short for /ar:proc)

List every autorun command with what it does, in this harness's spelling

Require justification for new files (short for /ar:justify)

Require justification before creating new files

Block a command pattern in this session

Allow a blocked pattern in this session

Plan export status and settings [on|off|globalon|globaloff|dir <path>|pattern <template>|rejected [on|off|dir <path>]|reset]

Unofficial KakaoTalk CLI and native MCP server for macOS — read, watch, and send messages via Accessibility automation.

Local-first AI action assistant for operators: memory, skills, tools, and permission gates to turn work into controlled action.

Agent-driven media library for your cloud drives (Quark 夸克 / 115 / 光鸭 GuangYa / 123网盘 / 天翼 Tianyi)

An open-source desktop AI agent built around Cyrene’s persona and powered by the self-developed Cyrene_Harness framework. It combines immersive character chat w…

在 Android 上运行的 AI 编程 Agent，内置 Linux 终端与代码编辑器，支持 MCP 协议扩展。

TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LL…

Floe — a native iOS/iPadOS AI agent workspace for iPhone and iPad, built for private bring-your-own-key workflows.

Spring Boot AI Agent — an out-of-the-box solution that makes your app converse, remember, think, and act.

Give your AI agent eyes for PDFs — structured text, tables, OCR, visual evidence, and page-level citations via MCP. Native Rust, local-first.

A tiny Claude Code skill that keeps your prompt cache warm during idle sessions, so your next message reads from cache instead of paying full price.

Monet — Multi-engine mission control for coding agents (Claude Code and Codex today). Browse, search, and drive your agent sessions from a native desktop app.

A DottedSign MCP server that enables AI assistants (Claude, ChatGPT) to manage signing tasks, templates, and document status via natural language.

Курируемый handbook по Claude Code на русском: hooks, skills, CLAUDE.md шаблоны, MCP-серверы, кейсы.

👾 Open Computer Use – Open-Source Alternative to Codex Computer Use

An open-source AI companion that actually remembers you — runs entirely on your own Mac or server. Desktop pet · long-term memory · proactive companionship · mu…

Graphical management tool for Kubernetes on desktop and mobile.

Open-source desktop app for content creation, with an agent runtime and standalone CLI.

Connect Claude and ChatGPT to KDAN PDF — upload, edit, compress, protect, redact, and compare PDFs in chat.

Ekko Studio is a local-first AI workspace for multi-agent chat, coding, and visual workflows, available on desktop and the web.

Open-source native iPhone/iPad client for OpenAI Codex CLI and Claude Code — review diffs, approve actions, steer sessions, and manage Git remotely.