LLM Mart Basic

Create a new skill in the current repository. Use when the user wants to create/add a new skill, or mentions creating a skill from scratch. This skill follows the workflow defined in .agents/skills/README.md and helps scaffold, validate, and sync new skills.

Use when reviewing a PR, API, IPC channel, endpoint, parameter, type, config, or architectural extension point that adds or expands shared surface area, especially when consumers are absent, exports are unused or speculative, existing consumers are hack-heavy, forward compatibili

Use when user wants to create a GitHub issue for the current repository. Must read and follow the repository's issue template format.

Create or update GitHub pull requests using the repository-required workflow and template compliance. Use when asked to create/open/update a PR so the assistant reads `.github/pull_request_template.md`, fills every template section, preserves markdown structure exactly, and marks

Automated Cherry Studio review for local branches, PRs, commits, files, architecture docs, and repository skills. Use for code or documentation reviews that need project-specific naming, main/renderer/shared placement and dependency rules, IpcApi and DataApi boundaries, lifecycle

Prepare a new release by collecting commits, generating bilingual release notes, updating version files, and creating a release branch with PR. Use when asked to prepare/create a release, bump version, or run `/prepare-release`.

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching,

Cherry Studio first-party tool and bundled-shell routing for general agents. For straightforward local work in shell-capable sessions, run JS/TS with `bun <file>` and one-off JS tools with `bun x`; run Python with `uv run [--with <pkg>] python` and one-off Python CLIs with `uvx`;

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist a

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's desc

从当前安装包查询 Cherry Studio 产品信息并排查运行问题。当用户询问功能、路由、快捷键、Provider、语言、Agent、频道、定时任务、Code CLI、当前版本，或报告运行错误、连接失败、配置异常并需要诊断时触发。

当用户明确要求搜索、安装、查看、卸载或创建 Skill，或内置 Skill / 工具出现能力缺口、无法完成当前任务时触发。通过 `mcp__skills__search_skills` 搜索并用 `mcp__skills__install_skill` 安装；已安装 Skill 的查看和删除通过产品清单导航到 Skills UI；没有合适结果时调用内置 `skill-creator` 创建并验证自定义 Skill，再继续原任务。普通任务仍先尝试内置能力。

收集、脱敏、预览并提交 Cherry Studio BUG、UI/UX 或功能反馈，默认提交到飞书。可在用户同意后调用内置诊断工具整理环境、错误日志、截图和用户导出的 trace，自动提交飞书表单或生成匿名上传 ZIP；也可安全解析反馈 ZIP 为表单字段。用户说“提交问题”“提交反馈”“上报 bug”“收集/上传错误信息”“整理日志/trace”“生成反馈包”，或描述 Cherry Studio 问题并希望记录时触发。只有明确要求 GitHub Issue 时才改用 issue-reporter。

Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code

将成功解决的用户问题收录到 FAQ 知识库。问题解决后自动判断是否收录。也可以在用户说"收录到 FAQ"、"记录这个问题"、"add to FAQ"时手动触发。

只在用户明确要求提交 GitHub Issue、GitHub Bug Report 或 GitHub Feature Request 时使用。用户只说“提交问题”“提交反馈”“上报 bug”“这是个 bug”或描述功能建议但未点名 GitHub 时不得触发，必须改用 cherry-studio-feedback 并默认提交飞书。

搜索、安装和协调创建 Claude Code Agent Skills。当用户想要搜索技能、安装工具、创建自定义 Skill，或者说"find a skill"、"搜索技能"、"帮我做个 skill"、"create a skill"时触发。也适用于用户说"有没有做 X 的工具"、"我想扩展 Agent 能力"，或当前能力不足需要先查找可复用方案的场景。

Imported from cherryhq/cherry-studio/resources/skills/skill-creator/agents/analyzer.md.

Imported from cherryhq/cherry-studio/resources/skills/skill-creator/agents/comparator.md.

Imported from cherryhq/cherry-studio/resources/skills/skill-creator/agents/grader.md.

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.

Turn a GAIA workflow misfire into a redacted, classified, filing-ready bug report in one read-only pass. Self-diagnoses config issues inline; files probable bugs upstream on confirmation.

Judge-the-form, human-gated hardening. Reviews recurring code-audit-frontend findings and, with approval, drafts the lowest-context-weight form (deterministic check / skill / path-scoped prose rule) into the working tree. Pass `list` to see live candidates or `why <finding_class>` to explain one.

Initialize a new project from the GAIA React template, renames, strips GAIA branding, configures i18n, installs Claude skills/plugins.

Plan a complex feature using GAIA's task-orchestration pattern, structures the work into fresh-context subagent phases for your approval. Does not implement.

Cut a new GAIA release, bump version, graduate CHANGELOG, regenerate manifest, open release PR, then tag on merge. Maintainer-only.

Detect and, on explicit consent, additively append the languages Serena is not indexing to the `languages:` list in `.serena/project.yml`, then prompt a Serena restart. Never mutates without a yes; inert without Serena.

Author an immutable SPEC artifact through Socratic discovery (spec-kit wrapper), then STOP. Terminal, never runs /gaia-plan; it prints a /gaia-plan prompt the human pastes into a fresh session. Pass `auto <description>` for non-interactive mode that answers its own questions.

Maintainer-only autonomous health audit + auto-heal loop. Runs N=3 fresh-team audit-fix-audit cycles with circuit breakers, reports an F-to-A+ verdict (folding in the shared Claude-integration fitness grade) or escalates.

Single post-init onboarding command; detects situation, runs only owed phases; safe to re-run. --reconfigure rotates token and re-selects tools.

GAIA before_specify hook: constitution placeholder check + spec-kit version-pin drift detection.

GAIA after_specify hook: immutability lint over the just-written SPEC artifact.

Close a plan after implementation+merge. Offers wiki-promote for the plan's consolidated SUMMARY.md, cold-consolidates an out-of-band merge, then early-reaps the local plan folder once cost is represented in cost.jsonl.

GAIA self-review: pre-gate-2 review pass on the in-progress SPEC draft.

Close a SPEC after implementation+merge. Optional drain of deferred wiki-promote, cold-consolidates an out-of-band merge into SUMMARY.md, then early-reaps the local SPEC folder once cost is represented in cost.jsonl.

GAIA Socratic discovery wrapper: /speckit-specify for the initial draft, then GAIA's own Socratic clarify loop.

GAIA before_implement hook: render PO-authored UATs into Playwright e2e specs at .playwright/e2e/spec-NNN/.

Promote merged SPEC or plan content into the GAIA wiki.

This project uses the GAIA preset. Bare `/speckit-clarify` is not the clarify path here: core clarify writes an off-shape artifact (a `## Clarifications` / `### Session` block with five-word answers) and carries a question cap GAIA does not use. Run `/gaia-spec` instead — it driv

GAIA-wrapped /speckit-specify: writes through core, then relocates the artifact to .gaia/local/specs/SPEC-NNN/SPEC.md and stamps GAIA frontmatter.

Show or configure the compact Fallow Impact statusline in Claude Code

An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作

Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

Transform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.

合乎周礼：DeepSeek-powered Zhouli-style Chinese translator, web app, and distributable Skill package.

This is a fork of the https://dockbox.dev project I made

🏆 Curated, ranked list of AI agent harnesses (100+) — plus an MCP server, llms.txt & JSON so agents can recommend them too. Rescored weekly.

A Python framework for modular, self-contained skill management for machines.

ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cogn…

AI Agent 驱动的开源可自部署视频工作台：将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿，支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video producti…

DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Autonomous Offensive Security, Bug Bounty & Red Teaming Agent Framework powered by Hermes Agent, specialized reasoning skills, and multi-model LLM orchestration…

⌥ Coding agent with the IDE wired in

Supercharge AI Agents, Safely

X (Twitter) Scraper API and X API Alternative. You do not need an official X developer account. You do not need to connect or use an X account for supported scr…

My AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.

Open-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.

观澜 / Guanlan：AI Agent 的中文互联网研究、阅读与信源路由工具。

Mac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.