LLM Mart Basic

Apply the Minimum Sufficient Work (MSW) principle through the MSW Kernel to scope, execute, verify, and stop agent work. State the requested outcome and smallest proof, admit a claim only when deleting it would leave the contract unmet or unproven, do and prove each necessary cla

Run an authorized task inside an Available Work Time (AWT) window with a shorter Closeout Grace Period (CGP), fixed deadlines, forecast checks, proportional convergence points, and a hard stop. Use when the user explicitly requests timeboxing, supplies an AWT/CGP pair, says AWT o

Apply the Minimum Sufficient Language (MSL) principle through the MSL Kernel to write anything a reader must act on. Bind the reader and what they already know, partition facts from the machinery that produced them, emit each admitted fact as an action, a verification, a judgment

Run the Codex Optimized Development, Evaluation, and Remediation (CODER) Loop with an orchestration-only coordinator, non-overlapping task-family owners, fresh independent reviewers, evidence-scoped remediation, and final coordinator acceptance. Discover and compose optional MSW,

Optimize ChatGPT Voice in the Codex desktop app into an ear-first control plane for free-form task coordination and opt-in workflows. Apply spoken synthesis, routing-only coordination, owning-task role contracts, project placement, explicit authority, safe speech, current-state v

Skill compilation specialist — the forge master. Use when the user asks to "talk to Ferris" or requests the "Skill Forge agent."

Initialize forge environment, detect tools, and set capability tier (Quick/Forge/Forge+/Deep). Use when the user requests to "set up" or "initialize the forge".

Discover what to skill in a large repo and produce recommended skill briefs. Use when the user requests to "analyze source for skills" or "discover skill opportunities."

Design a skill scope through guided discovery. Use when the user requests to "create a skill brief" or "brief a skill".

Compile a skill from a brief. Supports --batch for multiple briefs. Use when the user requests to "create a skill" or "compile a skill."

Fast skill from a package name or GitHub URL — no brief needed. Use when the user requests a "quick skill" or "skill from URL" or "skill from package."

Consolidated project stack skill with integration patterns — code-mode (analyzes manifests) or compose-mode (synthesizes from existing skills + architecture doc). Use when the user requests to "create a stack skill", "forge a stack", or "stack this project".

Smart regeneration preserving [MANUAL] sections after source changes. Use when the user requests to "update a skill" or "regenerate a skill."

Drift detection between skill and current source code. Use when the user requests to "audit a skill" or "audit skill" for drift.

Cognitive completeness verification — quality gate before export. Use when the user requests to "test a skill" or "verify skill completeness."

Rename a skill across all its versions — transactional copy-verify-delete with platform context rebuild. Use when the user requests to "rename a skill."

Drop a specific skill version or an entire skill — soft (deprecate) or hard (purge) with platform context rebuild. Use when the user requests to "drop" or "remove a skill."

Pre-code stack feasibility verification against architecture and PRD documents. Use when the user requests to "verify a tech stack" or "verify stack."

Improve architecture doc using verified skill data and VS feasibility findings. Use when the user requests to "refine skill architecture" or "improve architecture doc."

Campaign orchestration — multi-library skill production with dependency tracking, file-based state, and resume. Use when the user asks to "run a campaign" or "orchestrate skills."

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

Record the present state by mode — decision (ADR, RFC, rule), code (spec, doc, guide, scenario), or research (a ready report or one external material); a gate picks the document type.

First-time Archcore setup — wire host configs, measure the authored context, compose the full first-day seed in one preview, and create it on one confirm; import converts CLAUDE.md, AGENTS.md, rule files, ADRs, and docs into native documents; refresh adds new facts or drills into one domain.

Plan a feature or initiative through a computed route — a small fix exits with no documents, one capability gets a spec and a plan, a large initiative gets an umbrella PRD with one spec per capability; start with sdd, sources (market research), iso (regulated work), or research (technical investigation) to run that path directly.

Review branch changes against Archcore docs, or report project health; drift runs staleness detection, deep a full documentation audit, closeout closes a finished feature, experience captures a repeated pattern.

Verify that citations actually exist and that the claims they support are faithful to the cited source. Runs deterministic existence checks (Crossref / OpenAlex / Semantic Scholar / arXiv) plus a claim-faithfulness pass via the alterlab-citation-verifier skill.

Run a systematic, reproducible literature review on a topic and return an APA 7.0 annotated bibliography with a documented search strategy. Invokes the alterlab-deep-research pipeline in lit-review mode.

Run a full multi-perspective peer review of a manuscript, simulating an Editor-in-Chief plus three peer reviewers and a Devil's Advocate, and produce a structured editorial decision and revision roadmap. Invokes the alterlab-paper-reviewer skill.

Orchestrate the end-to-end academic research-to-publication workflow (research, write, integrity check, review, revise, re-review, finalize) with mandatory integrity gates and two-stage peer review. Invokes the alterlab-research-pipeline orchestrator.

Audit infra security: secrets, deps, CI/CD, webhooks, AI/skill files

Audit Solana program code for exploitable bugs and write a findings report

Compare per-instruction CU with the stored baseline to catch regressions

Build the web client (Next.js, Vite, React) and check env, types and bundle

Build Solana programs (Anchor, Pinocchio, native), incl. verifiable builds

Build the Unity project in batchmode for WebGL, desktop, Android or PSG1

Turn a solana-ai-kit fork into a project: set up CLAUDE.md, remove kit files

Un-ignore and commit the kit config dir, instruction file, .mcp.json and .gitmodules

Replay a user's failing transaction on forked state and map the error to source

Deploy a program to devnet, or to mainnet after the user's explicit go-ahead

Review the branch diff for Solana security issues, CU waste and AI slop

Read-only check of toolchain and kit config, with one fix-it command per failure

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.