LLM Mart Basic

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 this skill for Azure management-group hierarchy, subscription placement, resource-group boundary, and platform-versus-workload ownership decisions that affect governance, operations, and landing-zone scale.

Review Azure workload cost posture against the Well-Architected Framework Cost Optimization pillar: cost modeling, rightsizing, reservations, hybrid benefit, storage lifecycle, and idle resource elimination.

Review Azure workload reliability against the Well-Architected Framework Reliability pillar: availability targets, AZ/region topology, health monitoring, data resilience, deployment safety, and chaos testing.

Review Azure workload security posture against the Well-Architected Framework Security pillar: identity and access, segmentation, data protection, threat detection, secure development lifecycle, incident response, and policy compliance.

Use this skill when reviewing Backstage Scaffolder software templates. Trigger when the user asks whether a template is safe for developer self-service, whether template RBAC gates are in place, whether input parameters are validated, whether a step action has excessive blast rad

Use this skill for Cilium network policy review across the three policy formats (Kubernetes NetworkPolicy, CiliumNetworkPolicy, CiliumClusterwideNetworkPolicy), L7 policy via embedded Envoy, ClusterMesh cross-cluster semantics, Hubble flow observability, and CiliumEgressGatewayPo

用于对小说作者做"自我进化"蒸馏：①手动 / 周期回访（挖创作判断、捕获叙述原声（A 类）与创作判断原声（B 类）、周期蒸馏回填"作者小说风格画像"（十层）并反向净化防 AI 自创）；②全流程嵌入（选题构思 / 竞品 / 大纲 / 人物 / 背景 / 章节创作等全部环节自动调用，低频环节必采 1–2 问、高频草稿环节只读消费画像）；③散落触点（改稿痕迹 / 审阅回流 / 作者窗口 / 口述转写原声）；④像不像审计（原声句占比 / 惯用语命中 / 立场显影溯源 / 风格漂移，脚本取数）。与 通用-蒸馏作者文风 组成"静态种子 + 动态进化"双闭环，让写出来

用于围绕起点中文网或其他目标平台的同题材 TopN 候选池，按“市场数据层→内容创作层→运营策略层→受众反馈层”的四层框架锁定 3–5 本核心强样本并逐本深搜式竞对分析；若用户明确要求，也可对 TopN 全量逐本落盘。适合搜索榜单、筛选强样本、阅读目录/公开正文/设定/书评/读者评论/读后感/拆解材料，并在 `竞对分析/` 中为每部作品分别写出可举证、可横比、可回用于当前项目的详细竞对分析报告。关键词：竞对分析、竞品分析、标杆作品拆解、TopN 榜单、同题材对标、榜单深搜、四层拆解、读者评论分析、单书竞对报告。

用于创建连载小说章节正文、作者有话说与章节后记。适合新写单章、重写章节、扩写草稿、直接写回章节文件与完整跑通正文落稿工作流；其中 `## 作者有话说` 默认按读者向小剧场处理，不写成章节点评或创作总结。关键词：写章节正文、重写这章、扩写正文、作者有话说、章节后记、直接写回文件。

用于对章节正文做去 AI 味重写。适合主编式多轮去味、先诊断再定强度、整章去模板腔、局部拆解释腔、打散均匀句群、保信息重写与人物声音去同腔化。关键词：去AI味、主编式去味、多轮改稿、模板腔、解释腔、均匀句群、太像AI、重写这段。

用于做章节或片段的多平台适配策略。适合平台分发前的策略设计、改写前推演与平台撞车修复。关键词：多平台适配、平台差异矩阵、改写前推演、平台撞车修复、平台风格拉开。

用于对单章或多章执行多平台输出全流程编排。适合多平台输出 SOP、批量平台分发、断点恢复、门禁回炉与最终摘要收口。关键词：多平台输出编排、平台分发、断点恢复、门禁回炉、平台日志、最终摘要、今日头条。

用于对指定提纲执行"审阅→修改→复审"的闭环，直到双轴评分（技法分 ≥ 6.0 / 留存分 ≥ 5.0）加权的综合评分连续两轮独立审阅在保留两位小数后均严格大于 9.20。适合大纲审阅优化 SOP、报告复用、回炉循环、评分门槛控制与最终回执收口。关键词：大纲审阅闭环、回炉到 9.20 以上、双轴评分、复审循环、主报告覆盖、提纲优化 SOP。

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.

Analyze git diffs or staged changes and generate conventional commit messages that explain WHY a change was made. Supports auto-detecting type and scope, intelligent file staging, and interactive overrides. Use when asked to "write a commit message", "generate a commit", "describe my changes", "commit this", "summarize my diff", or "/commit".

SOC 2 compliance for Terraform — gap analysis, control implementation, evidence collection, and remediation guidance mapped to SOC 2 Trust Services Criteria.

Generate, review, secure, and test composite GitHub Actions following best practices — full repo scaffold, interview-driven generation, PR creation on existing repos, SHA pinning, secrets-as-inputs, job summaries, and actionlint validation.

Set up and troubleshoot Datadog — Agent deployment on Kubernetes, APM instrumentation, Log Management, Monitors, Dashboards, SLOs, Synthetic tests, and live incident investigation using the Datadog MCP server. Covers Terraform-managed Datadog resources.

Structured platform troubleshooting — classifies the problem layer, collects evidence, forms a root-cause hypothesis, and proposes a fix with validation and rollback steps.

Generate, format, and validate code documentation — docstrings, JSDoc, OpenAPI/Swagger specs, documentation sites, and developer guides.

Measure, benchmark, instrument, and debug DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, MTTR) for production engineering teams. Covers GitHub Actions instrumentation, Prometheus recording rules, Grafana dashboards, incident source integration, SaaS tool selection, and anti-pattern detection. Use when asked to "instrument DORA metrics", "benchmark our deployment frequency", "why is my MTTR data missing", or "generate a DORA dashboard".

Deploy and configure Dynatrace — OneAgent Kubernetes Operator, code-level instrumentation, Log Monitoring, custom metrics, SLOs, Dashboards, anomaly detection, Davis AI, and live incident investigation using the Dynatrace MCP server. Covers Terraform-managed Dynatrace resources.

FluxCD entry point — routes to the right workflow based on what you need. Live cluster issue → structured 5-workflow debug trace. Repo health check → 6-phase audit (discovery, validation, API compliance, best practices, security). Helm chart review → helmchart. Starts by asking one question to confirm the right mode.

Design, review, secure, and debug GitHub Actions workflows — reusable workflows, OIDC federation, SHA pinning, token scoping, promotion orchestration, and CI failure diagnosis.

Flux CD and Argo CD — two modes. debug: five structured debug workflows for live clusters (installation, source, HelmRelease, Kustomization, ResourceSet) producing a five-section report. audit: six-phase read-only repo analysis (discovery, validation, API compliance, best practices, security) producing a prioritised Critical/Warning/Info report.

Scaffold, lint, review, security-audit, test, and upgrade-verify Helm charts. Runs an interactive interview to build production-ready charts from scratch. Covers chart structure, values design, schema validation, kubeconform, helm diff, and multi-environment scaffolding. Use when asked to "create a helm chart", "lint my chart", "review my helm chart", "check helm security", "generate values schema", "run helm diff", or "add helm tests".

Design, install, debug, review, plan capacity, audit scaling history, migrate from Cluster Autoscaler, and upgrade Karpenter v1.x on EKS. Covers NodePool, EC2NodeClass, NodeClaim, Spot diversity, disruption strategy, Pod Identity/IRSA, interruption queue, private clusters, AMI rotation, and GitOps integration. Use when asked to "set up Karpenter", "debug why nodes aren't provisioning", "review my NodePool", "what would Karpenter provision for this workload", "why did this node terminate", "migrate from CA", or "upgrade Karpenter".

Design, debug, and review KEDA ScaledObject/ScaledJob autoscaling. Covers all major scalers (Prometheus, SQS, Kafka, Redis, Cron, HTTP Add-on, Azure Service Bus), TriggerAuthentication, scaling lifecycle tuning, GitOps integration, and troubleshooting. Use when asked to "add KEDA autoscaling", "debug why my ScaledObject isn't scaling", "review my KEDA config", or "generate a ScaledObject for <trigger>".

Find, live-validate, map the blast radius of, and revoke leaked secrets with Kingfisher (MongoDB) — across a local repo, Git history, a GitHub/GitLab/Bitbucket org, S3/GCS, Docker images, Slack, Jira, Confluence, Teams, or Postman. Covers local CLI scanning, direct validate/revoke without a scan, baseline management (track only new secrets), kingfisher.yaml policy, CI diff-scan gates, and pre-commit/Husky hooks. Use when asked to "scan for secrets", "is this key still live", "what can this credential reach", "revoke this token", "did we leak a secret", or "block new secrets in CI". Pattern-only secret scan bundled with a CVE pass → /platform-skills:trivy. Secrets-context safety in workflow YAML → /platform-skills:zizmor. Storing/rotating secrets inside the cluster → /platform-skills:secrets.

Cluster baseline scaffolding, RBAC diagnosis and generation, workload hardening, and structured pod/scheduling debug for plain Kubernetes across all distributions.

Generate, test, audit, debug, and migrate Kyverno policies using the new CEL-based policy types (ValidatingPolicy, MutatingPolicy, GeneratingPolicy, ImageValidatingPolicy — all apiVersion policies.kyverno.io/v1). Covers matchConstraints, matchConditions, CEL validations/mutations, generator.Apply(), Audit→Deny promotion, PolicyException, kyverno-cli testing, and migration from legacy ClusterPolicy or PodSecurityPolicy. Use when asked to "write a Kyverno policy", "test a ValidatingPolicy", "audit my cluster for violations", "why is my policy not firing", or "migrate from ClusterPolicy".

Linkerd-specific diagnostics — mTLS verification, proxy injection issues, authorization policy debugging, traffic management, and multi-cluster connectivity problems.

Linux administration and networking diagnostics — DNS, load balancing, VPCs, kernel tuning, and connectivity troubleshooting.

MCP server and client development — scaffold, implement tools/resources/prompts, validate schemas, debug protocol compliance, and deploy with auth and rate limiting.

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it.…

Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.

:memo: Vimlike Modal Text Editor in Rust

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

Hermes Agent memory plugin/provider for scope-aware recall, SQLite truth, LanceDB semantic search, and hybrid retrieval.

For You Agent——AI 时代的个人随身数字人格。把你的模型、AI 账号、技能、提示词和工作方式，带到每一个 AI 工具里。

A coding agent: give it a prompt and it reads, writes, runs commands, and searches code in a loop until the work is done, using native tool-calling across OpenA…

A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and…

Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption

DeepSeek Harness Desktop (dsh-desktop). EAC: Embracing All Creation (揽尽万象). Bundled Node.js runtime with full dsh-CLI kernel, one-click startup, 10 built-in UI…

See your agent think. Zero-config observability & governance for 26 AI agent runtimes: Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Cline, Ope…

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP…

Yet another coding agent harness, lightweight and written in go.

a coding Agent from pi. ∞ providers, sub-agents, hashline edits, and a permission gate

Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting…

🧠 Leon is your open-source personal assistant.

The Station, an open-world multi-agent environment that models a miniature scientific ecosystem.

The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. Makers of the AG-UI Protocol

VelaTerm = iTerm2 + Codex, The Best Terminal for AI Coding