LLM Mart Basic
@llm-mart · Joined Jun 2026
为现有前端项目幂等接入 Lovinsp 并验证点击定位源码能力。支持明确输入与结果回读。Use to integrate Lovinsp
Create a @deepseek-ai/dsh-* plugin package end-to-end — choose the extension point or capability seam, scaffold the package, implement the tool/hook/service, and run the repo gates. 触发:新增插件 / 加工具 / 开发 capability。
Publish a validated DSH plugin package (`@deepseek-ai/dsh-*` or `@lovstudio/dsh-*`) to npm, git, or tarball channels and verify it loads in the DeepSeek Harness. Use when the user asks to publish, release, or ship a plugin. 触发:发布插件 / 上架插件 / release dsh 插件。
清理冗余 CSS 并在现有 Tailwind 项目中重构样式。支持明确输入与结果回读。Use to refactor CSS and Tailwind
依据 README 更新 GitHub 仓库描述、主题标签及已核实的官网链接。支持明确输入与结果回读。Use to update a GitHub
分析任意语言项目的目录职责并渐进调整文件结构和引用。支持明确输入与结果回读。Use to improve a project directory
依据项目代码完善 README、安装说明、使用示例与真实品牌资产。支持明确输入与结果回读。Use to create or improve
检查 Next.js 页面元数据、索引规则、站点地图与分享展示。支持明确输入与结果回读。Use to review and improve
配置并备份 Agent 状态栏,支持列出历史版本和恢复。支持明确输入与结果回读。Use to update an agent status
汇总 Git 与项目日志中的检查点、时间范围和演进记录。支持明确输入与结果回读。Use to list a project checkpoint
根据当前 Git 差异和历史记录保存项目里程碑及后续事项。支持明确输入与结果回读。Use to create a project checkpoint.
Write, review, and maintain architecture decision records with clear context, alternatives, consequences, confirmation links, and lifecycle governance. Use when a consequential technical decision or its enforceable architectural constraint must remain understandable. Do not use f
Run a structured multi-agent debate by spawning a panel of expert agents on any question, with convergence-aware iteration and typed synthesis output via the `agent-council` CLI. Use when a decision has genuine tradeoffs, high stakes, or hidden assumptions worth adversarial colla
Design, run, review, or release framework- and vendor-neutral evaluations and observability for AI agents. Use when defining agent evals, datasets, graders, trajectory review, regression analysis, release gates, production traces, or privacy-aware telemetry. Covers task and traje
Operate an evaluated agent with tools and authority in production through a runtime control plane covering versioning, staged rollout, fallback, cost and latency budgets, tool health, human escalation, disablement, and trace-to-eval feedback. Do not use for building agents, desig
Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. It covers directory structure, SKILL.md metadata, progressive disclosure, evals, and repository conventions. Do not use this skill
Design and operate an organization's AI governance system: define governance principles, operating models and decision rights, risk frameworks, lifecycle gates, and fairness, transparency, privacy, security, regulatory, and board-oversight controls. Use when standing up a governa
Use when deciding whether an AI-enabled workflow should be adopted, scaled, constrained, redesigned, or retired, and the decision must connect business outcomes, worker or user effects, quality guardrails, full operating cost, telemetry, uncertainty, and accountable governance. D
Use this skill to create subject-neutral images and videos in an analog occultism / industrial CRT noir aesthetic: near-monochrome archival technical atmosphere, severe low-key lighting, tactile signal degradation, industrial geometry, and quiet unresolved tension. Use for portra
Convert Word (.doc/.docx/.docm), PowerPoint (.ppt/.pps/.pot/.pptx/.pptm/.ppsx/.ppsm), Excel (.xls/.xlsx/.xlsm/.xlsb), OpenDocument (.odt/.ods/.odp), RTF, EPUB, CSV, and PDF documents to clean GitHub-Flavored Markdown locally with the Any Doc CLI (npx -y @firecrawl/anydoc@0.2.4):
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.
/sync-automation-setup
Sync automation setup
Setup automated synchronization workflows
/sync-conflict-resolver
Sync conflict resolver
Resolve synchronization conflicts automatically
/sync-issues-to-linear
Sync issues to linear
Sync GitHub issues to Linear workspace
/sync-linear-to-issues
Sync linear to issues
Sync Linear tasks to GitHub issues
/sync-pr-to-task
Sync pr to task
Link pull requests to Linear tasks
/sync-status
Sync status
Monitor GitHub-Linear sync health status
/sync
Sync
Synchronize task status with git commits, ensuring consistency between version control and task tracking.
/system-behavior-simulator
System behavior simulator
Simulate system performance under various loads with capacity planning, bottleneck identification, and optimization strategies.
/task-from-pr
Task from pr
Create Linear tasks from pull requests
/tdd
Tdd
Test-driven development workflow with Red-Green-Refactor process and branch management
/team-workload-balancer
Team workload balancer
Balance team workload distribution
/test-changelog-automation
Test changelog automation
Automate changelog testing workflow
/test-coverage
Test coverage
Analyze and report test coverage
/testing_plan_integration
Testing plan integration
I need you to create an integration testing plan for $ARGUMENTS
/timeline-compressor
Timeline compressor
Accelerate scenario testing with rapid iteration cycles, confidence intervals, and compressed decision timelines.
/todo
Todo
Manage project todos in a todos.md file with add, complete, remove, and list operations
/troubleshooting-guide
Troubleshooting guide
Generate troubleshooting documentation
/ultra-think
Ultra think
Deep analysis and problem solving mode
/unity-project-setup
Unity project setup
Sets up a professional Unity project with industry-standard structure and configurations
/update-branch-name
Update branch name
Update current git branch name based on analysis of changes made
Your efficient agentic AI coding CLI assistant
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