LLM Mart Basic
@llm-mart · Joined Jun 2026
后端 API 工程师 Skill,执行服务端 API 层开发(路由、业务逻辑、鉴权中间件、缓存、队列),自动适配语言和框架
用户说“检查工作流是否安装正确”“为什么找不到 cm 命令”时使用。默认查询 npm 稳定版,有新版自动升级已管理的 CM 安装,再检查插件、核心 Skills、兼容包装与模板引用;不测试或修改业务代码。
智能合约工程师 Skill,执行合约开发、测试、部署,自动适配 EVM/Solana/Move 等链和开发框架
数据库工程师 Skill,执行数据模型设计、migration、查询优化,自动适配 ORM 和数据库类型
发布/运维工程师 Skill,执行 staging 部署、冒烟验证、发布记录与生产发布待决清单编制,自动适配部署栈;生产发布与基础设施变更强制人工确认
文档同步 Skill,开发完成后自动更新 README、.claude/ 配置、specs CHANGELOG,保持文档与代码一致
金融专家 Skill,覆盖 Web3 与证券/资产/交易领域的正确性审核、营销合规红线识别、合规问题清单生成、业务验收协同;把关型角色,只举旗不定性
用户说“修复这个可复现 bug”或要求根据失败报告修代码时使用。执行红灯测试、根因定位、最小修复、独立审查和回归;尚未确认的问题先用 cm-test,新功能和架构重设计转交 cm-prd。
前端工程师 Skill,执行前端开发任务,自动适配项目技术栈(React/Vue/Svelte/Next.js 等),支持 Figma/Stitch 设计稿还原
用户说“我有个点子”“帮我梳理产品”或需要先聊清目标时使用。通过逐题访谈整理为可交给 cm-prd 的 PRD;已有明确需求文档时改用 cm-prd,不写代码、不拆开发任务。
用户说“第一次接管这个项目”“分析仓库并生成项目规则”时使用。分析已有代码并生成 Codex AGENTS.md 与 CM/Claude 兼容规则;仅适用于非空存量项目,不创建脚手架、不承接普通代码修改。
微信小程序开发工程师 Skill,执行小程序开发任务,自动适配项目技术栈(原生小程序/Taro/uni-app 等),支持 Figma/Stitch 设计稿还原与云开发
用户说“把需求拆成可开发规格”“变更现有功能需求”或要求整理方案、任务和验收时使用。支持新项目、存量二开与需求变更;完成后停在人审规格,不直接编码。
产品经理 Skill,负责需求分析、用户故事与验收标准编写、歧义清单生成、变更影响分析、业务验收走查;把关型角色,不做技术设计与技术测试
QA 工程师 Skill,执行功能测试、E2E 测试、可视化回归、验收标准核验,自动适配项目测试框架
用户明确要求“只整理结构,不改变行为”时使用。执行边界分流、行为判官、分批重构和独立审查;缺陷修复转交 cm-fix,新增或变化的业务行为转交 cm-prd。
用户要查看或切换 CM 自动派发偏好、单/双 AI 声明、谁写谁审,或修改用户级运行时默认时使用。只管理运行时声明,不安装工具、不测试配额、不接管正在运行的任务。
用户运行 cm-security,或要求代码安全扫描、漏洞检查、密钥泄露排查、依赖漏洞检查时使用。默认检查当前分支相对主分支及已跟踪未提交修改,结合业务地图复核;--all 检查全部已跟踪文件。只报告问题,不自动修复、安装、升级或发布。安装自检用 cm-check,功能测试与覆盖率用 cm-test。
用户直接运行 cm-test、要求分析当前分支相对主分支的业务影响,或说“测试已有功能”“根据代码生成用例”“用浏览器走查”时使用。无参数分析已提交差异、单测覆盖率与回归重点;明确说“补齐单测”时连续补测并重跑、审查。显式目标保留原模式,不擅自修产品代码。
UI 还原工程师 Skill,把已确认的设计基准像素级还原为生产代码(token 先行、原子顺序、按交付形态量化验收:Web 用 BackstopJS、App 用 Maestro+模拟器截图);有基准才出场,不做业务逻辑
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.
A green PR, a controller reporting success, and not one line of the new code running
/lineage-discovery
Lineage discovery
Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)
/capture
capture
Triage raw inbox notes into reviewed repository destinations without deleting their sources.
/clean-ai-writing
clean-ai-writing
Audit and rewrite content to remove AI writing patterns
/content-shipped
content-shipped
Log a completed piece of content to content/log.md after the user confirms it was published.
/dream-apply
dream-apply
Validate a dream artifact, review each proposal, and apply only individually accepted changes.
/dream
dream
Run a curator pass against the validated memory directory and produce a proposal artifact.
/end
end
End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work
/find-context
find-context
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.
/migrate-gemini
migrate-gemini
Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.
/mine-gemini-workflows
mine-gemini-workflows
Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.
/reconcile
reconcile
Scan multi-session drift and offer individually reviewed fixes only after explicit approval.
/recover
recover
Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.
/setup
setup
Guided onboarding or import for durable workspace context
/start
start
Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers
/today
today
Create a morning heartbeat from repository state and update the local heartbeat log.
/update
update
Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session
/distribution-audit
distribution-audit
Maintainer-only. Find every file that would newly ship to adopters and decide, one file at a time, whether to ship it or withhold it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.
/gaia-audit
gaia-audit
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.
/gaia-debt
gaia-debt
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.
/gaia-fitness
gaia-fitness
Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
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