LLM Mart Basic

Use this skill when a NetSuite matter must be classified and routed to the right specialist agent, when a matter crosses multiple NetSuite domains and needs parallel review, when a live-account mutation intent must be gated, or when specialist agents disagree and the conflict mus

Use this skill to coordinate the order-to-cash process across Dynamics 365 Supply Chain Management, Finance, and Sales, covering confirmed order through fulfillment, invoicing, accounts receivable, and cash collection. It defines stage ownership, gate conditions, agent handoff ru

Use this skill to orchestrate the procure-to-pay (source-to-pay) process across Dynamics 365 Supply Chain Management, Finance, and compliance-aware separation-of-duties governance. It coordinates the journey from purchase requisition through purchase order approval, goods or serv

Use this skill to review the cross-tier seams of revenue-critical journeys — checkout, payment submission, account creation, and login — for idempotency of money-moving and account-creating requests, server-side re-validation of client-enforced rules, webhook duplicate/out-of-ord

Use this skill when a Salesforce specialist agent must hand a matter to another agent and the context, uncertainty, evidence quality, privilege posture, and privacy posture must survive the handoff intact. Defines the shared salesforce-case-capsule — a controlled, auditable excha

Use this skill when a Salesforce data exposure event has been detected or is strongly suspected. Triggers include: guest-user data exposure via Experience Cloud, cross-org data sync without a Data Processing Agreement, regulated-data sync in Marketing Cloud without a consent map,

Use this skill when any proposed mutation to a live Salesforce production org must be evaluated before execution. This is a refusal-by-default gate: if any required precondition is missing, the skill stops and refuses. Required preconditions are target_org_identity, environment_t

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

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.

Rollback deployment to previous version

Read project commands and documentation to optimize AI-assisted development process

Run CI checks and fix any errors until all tests pass

Perform comprehensive security assessment

Harden application security configuration

Capture and document session learnings

Setup automated release workflows

Configure CDN for optimal delivery

Setup complete testing infrastructure

Setup complete development environment

Configure code formatting tools

Configure Kubernetes deployment manifests

Setup code linting and quality tools

Configure load and performance testing

Setup monitoring and observability tools

Configure monorepo project structure

Implement API rate limiting

Setup visual regression testing

Open the Build with Claude contribution guide for writing a community story

Test and refine simulation accuracy with validation loops, bias detection, and continuous improvement frameworks.

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.