LLM Mart Basic

Autonomous task executor for spec-kit development. Executes a single task from tasks.md, verifies, commits, and signals completion.

Expert task planner for breaking plans into executable tasks. Masters POC-first workflow, task sequencing, quality gates, and constitution alignment.

This agent should be used to "create technical design", "define architecture", "design components", "create design.md", "analyze trade-offs". Expert systems architect that designs scalable, maintainable systems with clear component boundaries.

This agent should be used to "generate requirements", "write user stories", "define acceptance criteria", "create requirements.md", "gather product requirements". Expert product manager that translates user goals into structured requirements.

This agent should be used to "run verification task", "check quality gate", "verify acceptance criteria", "run [VERIFY] task", "execute quality checkpoint". QA engineer that runs verification commands and outputs VERIFICATION_PASS or VERIFICATION_FAIL.

This agent should be used to "update spec files", "refactor requirements", "revise design", "modify tasks after execution", "incrementally update specifications". Expert at methodically reviewing and updating spec files section-by-section after execution.

This agent should be used to "execute a task", "implement task from tasks.md", "run spec task", "complete verification task". Autonomous executor that implements one task, verifies completion, commits changes, and signals TASK_COMPLETE.

This agent should be used to "review artifact", "validate spec output", "check quality", "review research output", "review requirements", "review design", "review tasks", "review execution", "review prototype evidence". Read-only reviewer that validates artifacts against type-spe

This agent should be used to "create tasks", "break down design into tasks", "generate tasks.md", "plan implementation steps", "define quality checkpoints". Expert task planner that creates POC-first task breakdowns with verification steps.

This agent should be used to "decompose a large feature", "triage a big task", "break down into multiple specs", "create epic decomposition", or needs guidance on splitting large features into dependency-aware spec graphs.

dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters.

Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format. Use together with the dstack skill, and only when the user explicitly asks to create a preset or manage existing presets, not for deploying or serv

Use with the dstack skill for model-serving work when the image, serving command, resources, backend/fleet choice, or service behavior is not proven. Guides task-first prototyping on real hardware, choosing fleets/backends that can reuse idle instances and caches, checking vLLM/S

Extract semantic structure and transferable style grammar from academic figures, PDFs, and paper or figure URLs for analysis, redraws, or reference-conditioned generation. Do not use it for paper-text-only figure planning.

Unified academic figure designer, semantic color & surface decision engine, and FigureSpec v1 compiler. Handles style selection, reference palette derivation, colorblind-safe token binding, SVMC visual metaphors, and normalized compact prose prompt compilation across classic-tech

Plan evidence-backed figures for a paper draft, markdown notes, outline, manuscript, PDF, or paper webpage. Supports Draft-to-Figure fast-track for Markdown notes as well as comprehensive multi-figure planning for full manuscripts.

Plan, generate, inspect, and refine academic figures from repositories, papers, draft notes, paper URLs, PDFs, or reference images. Supports fast-track draft-to-figure generation and user passthrough mode.

Analyze ML, AI4Science, Systems, and research repositories into an evidence-backed semantic architecture graph for paper figure planning. Code serves as supporting evidence; paper narrative and user intent remain the primary source of truth.

Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route mes

Parallel-research-then-converge design workflow between two agents. Use this skill when the user wants two agents to independently think through a design problem before aligning on a solution — "spec X with codex", "design X together", "both agents think through X", "brainstorm a

A green PR, a controller reporting success, and not one line of the new code running

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

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.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

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.

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.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.

嘉立创EDA专业版(EasyEDA Pro)自动化：给 AI harness 装上画板的「手」—— 一套 typed 原理图/PCB 动作，CLI / Agent Skill / stdio MCP 三形态融合接入。承接嘉立创「不以卖板赚钱，以培养中国工程师为己任」 | EasyEDA Pro automation:…

Claude Code session log viewer for JSONL files in ~/.claude/projects. Browse conversations, tool calls, tokens, and live tail sessions on desktop, web, and TUI.

Shared memory MCP server — persistent, searchable, cross-client Claude, Opencode

OpenAI Codex CLI session log viewer for JSONL files in ~/.codex/sessions. Browse conversations, tool calls, tokens, collaboration chains, and live sessions on d…

High-performance Google Drive CLI and Model Context Protocol (MCP) Server for LLM/AI agents. Natively execute Google Apps Script (GAS) under a secure whiteliste…

"Vibe-Trading: Your Personal Trading Agent"

Local-first chat history analyzer with AI. | 本地优先的 AI 聊天记录分析工具

Official Oxylabs MCP integration

Persistent memory for Claude Code & Codex CLI. Auto-extracted knowledge graph, multi-representation embeddings, 3D WebGL visualization. LongMemEval R@5=97.45%.…

One person, a team of agents. Multi-session CLI that collaborates across terminals; /goal keeps long tasks running; WeChat/WeCom/Feishu gateway lets you call th…

AI 基础知识 - GPU 架构、CUDA 编程、大模型基础及AI Agent 相关知识。

Self-hosted, open-source agent skill registry for enterprises. Publish & version skill packages, govern with RBAC and audit logs, deploy on-premise with Docke…

深度调研报告生成 Skill — 一条命令，十分钟出券商级深度调研报告 / Professional deep research report generation Skill · Supports 19 languages

The OKF toolkit for Claude Code — author, maintain, validate & visualize Open Knowledge Format bundles. Plugin, agent skills, and a GitHub Action.

Autonomous AI pentesting agents — real-time reconnaissance, vulnerability detection, and exploitation orchestration. Go + TypeScript.

Native macOS and iOS App for the Hermes AI agent — multi-window, multi-server (local + remote over SSH). Chat, dashboard, sessions, memory, cron, MCP, and more.

Multiplayer Claude Code and Codex. Self-hosted team workspace for Claude Code and Codex. Multi-user, browser-based, AI mates with memory.

Every past session, subagent, and workflow -- queryable by your agent, browsable by you

盯盘侠 PanWatch · 自托管 AI 盯盘助手，集成 TradingAgents 多 Agent 投资决策 | A股/港股/美股实时监控、持仓管理、智能分析、全渠道推送