LLM Mart Basic

Generate professional slide deck images from content (Markdown, text, URLs). Creates outlines with style instructions, then generates individual slide images. Supports 16 visual styles, CJK/Latin mixed text, branding overlays, and PPTX/PDF export. Use when the user asks to "creat

Convert PDF files to a single vertically concatenated PNG image using macOS native CoreGraphics. Each page is rendered at 2x scale and stitched top-to-bottom. ~20x faster than pdftoppm+ImageMagick, zero external dependencies on macOS. Trigger when the user mentions "pdf to png",

Convert PNG images to high-quality SVG with optional white-background removal, vtracer spline vectorization, and svgo compression. Use when the user asks for "PNG to SVG", "png2svg", "转 SVG", "矢量化", "去白底", logo tracing, or converting raster icons into editable vector assets.

Orchestrate a complete investor BP workflow or route to one focused module: source-backed outline, PPTX/PDF production, or evidence/content/visual polishing. Use when the user wants to create a business plan end to end, combine BP stages, continue from an existing BP workspace, o

Turn existing project materials into a source-backed investor BP brief, evidence ledger, and 12–15 slide outline. Use before making slides, when the product positioning is unclear, or when an existing outline is too technical, generic, or unsupported. Trigger on "写 BP 大纲", "融资叙事"

Turn an approved investor BP outline into a clean, professional slide deck with deliberate style selection, real product evidence, charts, branding, PPTX/PDF, and a full-deck preview. Use when the narrative already exists and the user wants PPT production, visual style exploratio

Review and improve an existing BP outline, PPTX, PDF, or rendered slide set across investment logic, evidence, copy, charts, and visual quality. Produces a scored report, page-level revisions, and targeted regeneration instructions while keeping facts separate from assumptions. T

Generate complete business proposals for client projects from requirements.

Create research-backed product and technical solution plans from a user's requirement. Use when the user asks for detailed feasibility analysis, technology selection, architecture, implementation roadmap, library/vendor comparison, "解决方案", "技术方案", "产品方案", "选型", "调研分析", or a Skill

Professional-grade contract review skill that adds comment-based issue annotations without changing original text. Enforces a four-layer review (entity verification, basic, business, legal), writes structured comments (issue type, risk reason, revision suggestion) with risk level

Extract invoice data from images or text descriptions and generate a categorized Excel expense report. Supports receipt photos, scanned invoices, and manual text input. Auto-classifies into: business entertainment (客户餐费), travel-transport (机票/火车票/打车), travel-accommodation (酒店), t

Generate a complete professional event plan from guest background material.

Use when the user needs multi-source research with citation tracking, evidence persistence, structured report generation, or an implementation landscape that includes GitHub and other open-source forges. Triggers on "deep research", "comprehensive analysis", "research report", "c

Write multi-chapter books end-to-end from an outline.

Export WeChat Official Account articles into reusable structured content.

Polish and elevate MBA thesis / dissertation to national outstanding thesis quality (全国优秀论文). Performs comprehensive improvement: academic language, argument structure, logical rigor, innovation highlights, and formatting. Input: markdown thesis text. Output: polished full text.

Audit and optimize one or more existing Agent Skills from a canonical source path, then bump semver, update README/SKILL.md/skill.yaml/CHANGELOG.md, and verify installed copies and catalog synchronization. Checks frontmatter, trigger quality, CLI hygiene, naming, portability, ver

Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.

Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.

Design docs that reduce cognitive load. Trigger: writing guides, READMEs, RFCs, onboarding, architecture, or review-facing docs.

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.

Check frontmatter against the schema

Pull knowledge into a project

Scan for credentials

Show what a claim rests on

Split an overloaded page

Find concept pages nobody has touched

Audit the tag vocabulary

How my sources developed over time

Show which pages an answer used

Add relation types where they matter

The weekly review

Implement an approved plan or issue in its own worktree, run the gate, open the pull request.

Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.

Write the repository handoff file for the next session, and record any durable learning.

Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.

Turn a topic or issue into a plan the reviewer approves in the native plan pane.

Answer a research question with parallel read-only gatherers and one synthesized digest.

Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.

Transform a vague prompt into precise, structured AI instructions

Implement an approved plan or issue in its own worktree, run the gate, open the pull request.

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…