LLM Mart Basic

今日头条爆款内容查询 — 输入关键词搜索今日头条最新作品（图文/视频），支持按阅读量/时间排序、限定时间范围，终端表格展示 + CSV 导出 + 交互式 HTML 报告。当用户需要搜索今日头条热门内容、追踪头条热点、分析爆款文章时使用。

X(Twitter)作品评论分析工具。输入推文链接或推文ID即可获取一级评论数据，支持游标翻页，并进行四维情感分析（积极/负面/需求/竞品）。当用户需要查看X(Twitter)推文评论、分析推文舆情、了解用户反馈时使用。触发词：X评论、Twitter评论、推文评论、X作品评论分析、评论查询、评论分析、评论舆情、看评论、twitter评论、X推文。

X(Twitter)视频下载 — 粘贴 X(Twitter) 视频链接，一键解析返回无水印视频下载链接。当用户需要下载 X(Twitter) 视频、保存推特视频、获取 X 视频直链时使用。触发词：X视频下载、Twitter视频下载、推特视频下载、X视频解析、Twitter视频解析、下载推特视频。

输入关键词搜索X(Twitter)作品，支持按热门、最新、媒体、用户、列表五种类型精准筛选，一键获取作品正文、互动数据、媒体附件与作者信息等结构化结果。触发词：当用户提到'X搜索'、'Twitter搜索'、'作品搜索'、'X关键词搜索'、'搜一下X上的'时使用

短视频下载器 — 支持抖音、小红书、快手、视频号、B站、YouTube、Instagram 等主流平台无水印视频下载。

帮助用户编写专业级 AI 视频提示词，写完直接生成 MP4 视频。支持多种创作场景与问题诊断，确保提示词准确可执行。触发词：视频提示词、视频生成提示词、AI视频创作、写视频提示词、导演指令、文生视频提示词、视频脚本、生成视频

图文运营创作器。从选题、撰写、配图到质检，一条龙完成运营文章生产。看到好文章能仿写，给个 Skill 能生成推广长文，写完正文能自动配图。内置写作质量管控与自动配图能力，图文一体交付。触发词："生成运营文章"、"链接仿写"、"对标分析"、"Skill 推广"、"为正文配图"。

公众号账号诊断工具是对任意公众号账号进行四维度量化评分（内容健康度、用户活跃度、内容核心数据、运营规范性），对标行业平均水平，输出可落地的运营优化建议。

AI视频号信息源 — 每日自动扫描视频号 AI 相关作品，按互动量（点赞/分享/评论）筛选最火内容，智能聚类生成精美 HTML 日报，支持封面图、数据指标和每日订阅。当用户需要 AI 视频号日报、视频号AI热点、AI视频号内容、视频号信息源时使用。

公众号爆款封面AI设计工具。基于全网每日收录的10w+文章数据，获取同赛道爆款封面视觉元素，通过AI分析总结高转化视觉规律，生成贴合文章内容、符合平台流量审美的封面设计方案。当用户设计公众号封面、生成封面方案、查询爆款封面规律时使用。触发词：公众号封面、封面设计、爆款封面、封面方案、封面生图。

每日账号推荐速览直接对接官方最具“黑马体质”的阅读增长榜单，按日期查看公众号阅读增长率TOP榜。每个作者只展示最高阅读那篇，标题做成可点击链接，一秒直达原文。

一位公众号爆款文案撰写专家。具有硬核的公众号文案功底，不管给你什么文案，你总能把该文案转化为一篇高阅读数的公众号文案，文案中必定会包含一些具有公众号特色的词汇。这个角色需要具备精通语言的能力，这个角色的任务是通过语言的艺术表达，使句子更加生动、吸引人、有趣和具有说服力。

公众号热门账号推荐快速获取微信公众号综合实力排行榜TOP50，支持按日榜/周榜/月榜及垂直领域筛选，展示综合评分以及详细数据。支持深度分析单个账号、导出HTML可视化报告、订阅日/周/月榜推送。当用户需要查询公众号实力排行、按时间或领域筛选、查看互动指标、获取榜单解读、导出图表或接收定期推送时使用。

一键解析视频号视频的真实下载地址。粘贴视频号分享链接，即可获取视频标题、封面图和高清无水印下载地址。触发词：当用户提到'解析视频号'、'视频号下载地址'、'视频号下载'、'视频号无水印下载'时使用

公众号文案创作工具。基于红狐数据公众号爆款雷达每日收录的热门文章，按关键词检索爆款、分析流量规律、生成可发布的完整文章。当用户写公众号文章、生成公众号文案、查找爆款文章、分析爆款规律时使用。触发词：公众号文案、公众号爆款、爆款文章、公众号写作、公众号文章生成。

微博评论分析工具。输入微博博文链接即可获取一级评论数据，支持分页浏览和四维情感分析（积极/负面/需求/竞品）。当用户需要查看微博评论、分析评论舆情、了解用户反馈时使用。触发词：微博评论、博文评论、评论查询、评论分析、看评论。

X(Twitter)每日最具影响力账号榜单追踪分析工具；每日早上9:00更新前一天榜单，最多回溯7天；支持性别（男/女/全部）与32个行业分类筛选、分页翻页、HTML可视化报告导出与定时订阅推送；当用户需要查询X/Twitter账号排名、热门账号榜、分行业/分性别榜单、下载榜单报告或订阅推送时使用。触发词：X榜单、Twitter榜单、推特账号排名、X热门账号、Twitter影响力榜、推特大V排行。

Your AI coding harness, ported to every client you use. Capture Claude Code (or Codex) rules, hooks, skills, subagents, commands and MCP servers once; apply the…

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📚 给中国律师/法务的一站式开源 AI 工具地图｜200+ 个 gh 核验开源仓·按工作场景分类·能否商用标注｜awesome list

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.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…