LLM Mart Basic

Write warm, direct collaboration comments. Trigger: PR feedback, issue replies, reviews, Slack messages, or GitHub comments.

Use Gentle AI harness discipline for Pi work: clarify first, preserve OpenSpec artifacts, use strict TDD where available, delegate through subagents when useful, and protect review workload.

Create and triage GitHub issues from repository evidence. Trigger: issue creation, bug reports, feature requests, or issue approval.

Trigger: judgment day, judgement day, dual review, adversarial review, juzgar. Run explicit blind dual review with at most two scoped fix/re-judgment rounds.

Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.

Trigger: /skill-creation, skill creation, skill creator, create skill, new skill. Create LLM-first skills with valid frontmatter.

Trigger: improve skills, audit skills, refactor skills, skill quality. Audit and upgrade existing LLM-first skills.

Trigger: update skills, skill registry, actualizar skills, after skill changes. Index available skills by trigger and path.

Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.

Master router for the SOTA engineering skills library. Use this skill whenever the user asks to build, design, implement, refactor, harden, optimize, review, or audit an application, service, or codebase and the request spans more than one domain — or when you are unsure which sp

State-of-the-art API design and audit guidance (2026) covering REST/HTTP, GraphQL, gRPC, WebSockets/SSE/realtime, webhooks, versioning/evolution, and API security/operations. Use when designing or building any API surface (endpoints, schemas, protos, realtime channels, webhook se

State-of-the-art software and system architecture rules (2026) for both building and auditing. Use when designing, building, refactoring, or extending system architecture — boundaries, DDD, hexagonal/clean architecture, event-driven design, CQRS, sagas, messaging, caching, shardi

State-of-the-art rules for writing and auditing asynchronous and concurrent code across runtimes (Python asyncio, JS/Node, Go, Rust, JVM). Use when building anything with async/await, threads, processes, event loops, task groups, channels, or queues — and when auditing existing c

State-of-the-art C and C++ engineering rules (2026 baseline) that Claude applies when writing or auditing C/C++. Covers modern idioms (RAII, value semantics, smart pointers, C++23), memory safety (lifetimes, bounds, sanitizers, hardening flags), undefined behavior, security (SEI

State-of-the-art CLI and developer-tool UX guidance (2026) covering command and flag design, output and interaction (stdout/stderr, --json, TTY detection, exit codes, prompts), runtime behavior and lifecycle (signals, dry-run, idempotency, XDG paths, completions, telemetry), and

State-of-the-art cloud infrastructure architecture (2026). Applies when designing, building, or auditing cloud environments on AWS, GCP, or Azure — account/project structure and landing zones, IAM and workload identity, VPC/network design, DNS/TLS/CDN, compute selection (serverle

Secure coding and security auditing rules (2026 baseline). Use whenever BUILDING or modifying code that crosses a trust boundary — endpoints, handlers, auth/login/signup, sessions, JWT/OAuth, file uploads, payments, multi-tenant features, crypto/secrets handling, parsers, CLI/exe

State-of-the-art confidential computing and cryptographic PETs (2026) for BUILDING and AUDITING systems that protect workloads and data in use from the infrastructure they run on — the inverse of sandboxing. Covers TEE selection (AMD SEV-SNP, Intel TDX, ARM CCA realms, SGX enclav

State-of-the-art marketing copywriting and content guidance (2026) covering positioning and value propositions, headlines and landing-page copy, CTAs and social proof, SEO content (search intent, E-E-A-T, Google spam policies), and the accuracy/legal layer — claim substantiation,

State-of-the-art data engineering rules (2026) for building and auditing data pipelines and analytics infrastructure. Covers architecture and modeling (ELT, lakehouse vs warehouse, dimensional models, medallion layering), pipeline and orchestration discipline (idempotency, increm

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

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.

{{SKILL_ENTRY:post-merge-cleanup}}

Show the codeArbiter command catalog — the public command list and what each routes to.

{{SKILL_ENTRY:commit-gate}}

Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

{{SKILL_ENTRY:context-check}}

{{SKILL_ENTRY:context-creation}}

{{SKILL_ENTRY:debug}}

{{SKILL_ENTRY:decompose}}

Verify the active host install, package, command ownership, enforcement{{IF:pi}}, wrapper self-test, and active-dispatch coverage gap{{ELSE}}, and harmless live-fire probe{{END}}. Read-only.

Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.

Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.

Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.

Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.

Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.

{{SKILL_ENTRY:finishing-a-development-branch}}

Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.

Trim transcript clutter to extend session lifetime — analyze, prune a copy, or toggle the after-each-turn service. Dry-run by default; gains land at resume/compaction, not the current turn.

{{SKILL_ENTRY:decision-variance}}

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.