LLM Mart Basic

商品短视频广告。卖点 → 分镜脚本 → 分段生成 → 拼接加字幕成片。当用户说「做条广告」「短视频」「投流素材」「分镜脚本」「带货视频」时使用。

去水印去文字。带水印 / 文字 / logo 的图 → 干净图，背景纹理自然补全。当用户说「去水印」「去文字」「擦掉 logo」「把字去了」时使用。

平铺图转隐形模特立体图。平铺图 → 有体积感与版型的立体展示图。当用户说「转 3D」「立体图」「隐形模特」「把衣服撑起来」时使用。

UGC 口播种草视频。商品 + 人设 → 口播脚本与成片，达人自拍质感。当用户说「口播视频」「种草视频」「达人风格」「UGC」「真人推荐」时使用。

鞋包配饰真人穿戴图。商品图 + 模特参考图 → 真人佩戴图，落位、透视与阴影自然。当用户说「鞋包上脚」「配饰上身」「墨镜戴上」「首饰佩戴图」「包包上身」时使用。

Apply WIT (Writing Is Thinking) as a human–LLM collaborative scientific reasoning skill for scientific question formulation, finding-driven research planning, next-experiment selection, Results or Discussion review, claim–evidence and reviewer stress tests, manuscript logic audit

Use when creating skill repositories, standardizing or validating skill repo structure, setting up composer/release workflows, configuring split licensing (MIT + CC-BY-SA-4.0), fixing plugin.json / SKILL.md validation or version-parity errors, or releasing a skill version (versio

Conversational design workshop for substantial work. Interviews the human one question at a time, explores 2-3 approaches with trade-offs, and presents the design section by section for approval before writing only design.md, then stops. Combines requirements discovery with codeb

Post-implementation completion workflow for Spec-backed Plans. Use after spec-implement completes to validate, review, create stacked commits, and open a PR via code-pull-request. Triggers only with an active Spec-backed Plan after spec-implement completes, including when the use

Continue an approved Spec-backed workflow when the user says "implement", "go", "start", or "do it". After Codex Plan Mode, persist the next missing design.md or plan.json artifact and stop. When both artifacts exist, execute plan.json with TDD and report between batches.

Write approved implementation plans in one of two modes. Explicit Inline mode creates a conversational plan for bounded work. Spec-backed Plan converts an approved design.md into plan.json. Both modes stop after producing their plan output. Trigger after atelier-orchestrator sele

Skill routing and workflow orchestration. Selects Inline Plan or Spec-backed Plan, routes to the correct workflow skill, and manages transitions between phases. Use when starting any conversation or task to determine which planning mode and skill apply.

Configure a repository for Atelier's development workflow. Use only when explicitly invoked; inspect existing guidance, issue-tracker and domain-document conventions, preview the proposed configuration, and write only after approval. It does not install Atelier or initialize exte

Disciplined debugging methodology. Triggers on bug reports, test failures, "debug this", "diagnose this", unexpected behavior, build failures, integration issues, or performance regressions. Find root cause before a permanent corrective fix; contain urgent harm safely first.

Grill the user relentlessly about a plan, decision, or idea, maintaining the project's domain model (CONTEXT.md, ADRs) as decisions crystallise. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.

Generate and validate conventional commit messages following the conventionalcommits.org spec. Use whenever the user wants to commit code, mentions commit messages, git commit, or asks to create a commit. Triggers on "commit", "git commit", "conventional", or when reviewing commi

Compact the current conversation into a handoff document for another agent to pick up.

Manage GitHub pull requests or GitLab merge requests: create, read/leave/respond to comments, and merge. Triggers on "open a PR", "make a PR", "merge this PR", "merge the MR", "read PR comments", "leave a comment on the PR", "respond to a comment", "ship this", or when a feature

Multi-agent code review with parallel specialized reviewers, architecture validation, challenge validation, and durable handling of previously decided findings. Use `rq` to request a review of diffs (defaults to main branch), `rs` to respond to findings and record intentional non

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.

Daily standup: all 9 departments report on the current project in parallel

Identify skills injected where not needed, propose regex and description tightening

Draft X/Twitter announcement post (or thread) for the latest plugin release

Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste

Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes

Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization

Propose a skill revision and compare fresh executions under a frozen rubric

Prune stale entries from the whetstone sync decision log

Bump version, commit, push, mirror to ai-skills, and update local plugin

Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).

Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns

Triage all open PRs with parallel agents, label, group, and review one-by-one

Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).

Create Architecture Decision Records with format selection and lifecycle management

Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps

Explore requirements and approaches through collaborative dialogue before planning implementation

Create engaging changelogs for recent merges to main branch

Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps

Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.

Record a video walkthrough of a feature and add it to the PR description

PiG (Pi in Go) is a faithful Go port of upstream Pi, the TypeScript codebase behind the Pi coding agent. It is a parity-bound translation, not a rewrite: upstre…

An AI Agent that lives in your pocket. Local-first and privacy focused.

Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.

Adaptive Test-time Learning and Autonomous Specialization

Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests

Knowledge Management for Humans and Agents

Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs…

DeepAgent Code: AI coding agent with persistent memory and control plane

Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.

CLI for Telegram — agent-friendly, daemon-based, with webhook event push.

AI deep-research agent that turns any question into a cited report: plans searches, reads real sources, verifies evidence. Self-hosted, multi-provider, Docker-r…

Event-stream AI Agent framework for building your persona bot 🍊

Give the agent a machine. Just not yours. Each AI coding agent gets its own isolated machine with root, Docker, and systemd - active defense detects and stops t…

Local Emperor-style AI agent with Vue WebUI, multi-provider LLMs, streaming chat, tools, skills, memory, and token telemetry.

Open-source AI reverse-engineering agent platform and MCP server for Ghidra, Frida, x64dbg and Rizin — automated PE/APK/binary analysis, CTF and malware researc…

"Never send a human to do a machine's job" - Open Source AI hacking agent

Prismer Cloud

My Personal Blog (Robotics)

Tau Coding Agent - like Pi, but twice as much

Open-source alternative to OpenAI Dots: self-hosted AI chat, tools, approvals, connectors, and computer tasks.