LLM Mart Basic

Use this skill when reviewing Azure Key Vault certificate issuer configurations for cert-manager on AKS. Trigger on any request to audit Key Vault certificate policies, Managed Identity role assignments, exportability settings, private endpoint connectivity, integrated CA credent

Use this skill for Azure landing-zone design, management-group and subscription hierarchy reviews, platform-versus-application boundary decisions, or multi-subscription Azure platform architecture critiques that span governance, identity, networking, security, and operations.

Guard live AKS deployment rollouts with PDB audit, maxUnavailable/surge validation, rollout pause/undo gates, and post-rollout health verification.

Guard live App Service slot swaps with sticky-settings audit, warmup probe verification, swap-with-preview staging, and instant rollback posture.

Guard live ARM, Bicep, and Deployment Stack changes with what-if evidence, denySettings review, changeset diff, rollback posture, and approval gates.

Gate Azure budget action changes and GPU/HPC SKU provisioning against approved spend limits, with quota audits and emergency spend-stop playbooks.

Guard live permanent Microsoft Entra ID and Azure RBAC role assignments with scope audit, principal-type risk classification, dangerous-role detection, and explicit approval gates before write. Use only when a direct (non-PIM) role assignment is intentionally requested against a

Guard Key Vault key rotation, rotation policy changes, soft-delete enforcement, and purge-protection enablement with irreversibility warnings and rollback evidence.

Gate Entra ID PIM eligible role activations with justification, MFA, ticket binding, time-bound scope, and approval workflow gates before any privileged Azure role becomes active.

Use this skill to classify a user task, select the right Azure specialist agent or team of specialists from the catalog, and dispatch them. Single specialist for focused single-domain tasks; parallel team (max 4) for tasks that span multiple domains. Never auto-dispatches live-gu

Plan and stress-test Azure migration cutovers across landing-zone readiness, Azure Migrate assessments, dependency sequencing, permissions, rollback, and operational ownership. Use when a migration plan needs a go/no-go verdict instead of vague optimism.

Use this skill for Azure network architecture review, hub-spoke critique, routing and DNS dependency analysis, shared-services boundary decisions, firewall placement review, and landing-zone connectivity guidance.

Use this skill for Azure Monitor, Log Analytics, Application Insights, alerting, KQL triage, telemetry-gap analysis, workbooks, or operator-grade incident and posture investigations.

Design and review Azure platform automation and DevOps delivery for landing zones, shared platform services, and safe infrastructure rollout flows. Use for IaC approach selection, Bicep versus Terraform positioning, bootstrap/run phase separation, pipeline control design, secret-

Use this skill for Azure Private Link and private endpoint adoption planning, including hub-versus-spoke placement, private DNS zone linkage, route implications, centralized versus workload-local endpoint trade-offs, and safe rollout validation.

Use this skill for Azure RBAC, Entra-backed access, role assignment, custom role, scope, subscription, management group, or least-privilege review tasks. Trigger when the user asks whether Azure access is too broad or how to grant access safely.

Use this skill for Azure resilience, business continuity, and disaster recovery reviews covering RTO/RPO realism, failover and failback assumptions, shared-responsibility gaps, and recovery runbook or drill quality.

Use this skill for Azure Resource Health, Service Health, activity-log alert, and first-pass incident triage when the question is whether Azure platform health is part of the problem.

Use this skill when the user asks which Azure role to assign, how to grant minimum access, whether a built-in role is sufficient, or when a custom role may be required.

Use this skill for Azure security posture review, baseline hardening, managed identity adoption, Key Vault posture, private access decisions, Azure Policy guardrails, and logging or audit gap analysis. Trigger when the user asks how to harden an Azure workload or platform without

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

Offline-first Python AI agent that runs a tiny research business: quotes each job against its own costs, collects via Stripe, fulfils with NVIDIA Nemotron, pays…

DSH 插件 · 注入式优化器 0.8（主线）：你照常说话，它在你发送后,AI接收前把"这一轮到底要什么"理清楚，再把这份理解交给工作 AI(上下文注入) —— 原话不改写，条条带逐字依据。含控制界面（档位/权限/模型/上下文/只读工具）、拦截浮层（思维层+产出层）与真实 token 用量。可明显提升大多数模型的发挥稳…

Reliable AI Skill + MCP toolkit for agent-driven desktop CAD automation.

Curated real-world use cases for Hermes Agent — the self-improving AI agent from Nous Research. Backed by primary sources.

AI Agent 教学仓库 | 系统化 LangChain、RAG、LangGraph、MCP 全栈实战代码 | 万字博客详解 | 开源可运行示例 | 从零构建智能体

从 0 复刻 WorkBuddy-style 桌面 AI 助手 Harness：24 章 Python 教程，覆盖 Agent Loop、工具调用、记忆系统、Sidecar、沙盒审计、DeepSeek/OpenAI 评测轨迹

MCP server and CLI tools for web search and crawling, built on SearXNG and Crawl4AI

Delta MCP is a free app that sits between your AI apps and their MCP servers: one program per task instead of one tool call per step, up to 24.1× fewer tokens i…

Ava turns any Android 5+ device into a voice-first Home Assistant kiosk. Native C++ under the hood, so a 10-year-old tablet still listens, talks, and runs the h…

Roblox Studio macOS Window Capture Fix 2026: Real Screenshot Tool Instead of Magenta Playtest Glitch

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