LLM Mart Basic

Review code for correctness, clarity, and security.

Write clean, correct, production-quality code.

Evaluate trade-offs, document options, and justify recommendations.

Read, create, edit, and organize files and directories.

Work with GitHub branches, PRs, issues, and reviews via the gh CLI.

Break problems into steps, identify dependencies, and estimate scope.

Gather information, evaluate sources, and synthesize findings.

Use skillfold to manage project and user skills for Claude Code, Codex, and Cursor. Declare skills in skillfold.yaml, pin them in skillfold.lock, and install them reproducibly.

Condense information with audience-appropriate detail levels.

Write and reason about tests, covering behavior, edge cases, and errors.

Produce clear, structured prose and documentation.

Implements code incrementally with quality gates. Use when the user says 'build' or 'implement', or when starting the implementation phase of an approved plan.

Monitor the CI pipeline for the current branch via a background Monitor script (GitHub or GitLab), reacting to pass, fail, and manual-gate states. Use when the user says 'watch CI', 'monitor the pipeline', 'is CI green', or after pushing a branch or creating a PR/MR.

Runs a structured production-incident investigation that forces evidence-first hypothesis ranking before any code change. Use when given an error message, Sentry alert, failing log, or an 'investigate <X>' request.

Creates or updates a diagram, picking mermaid vs drawio per rules/diagrams.md, writing the source file, and previewing via MCP. Use when the user says 'diagram' or '/diagram', or asks for a flowchart, architecture, sequence, or state diagram.

Drives a fleet of MRs/PRs to done with a manager loop plus the built-in /goal command, delegating all edit, review, rebase, and conflict work to worktree-isolated domain-expert subagents. Use when the user says 'drive fleet' or 'drive the fleet', has 2+ independent lanes to drive

Investigates and fixes a GitHub issue. Use when given an issue number or URL, or when the user says 'fix issue'.

Runs a grilling session that challenges a plan against the existing domain model, sharpens terminology, and updates the CONTEXT.md glossary inline as decisions are made. Use when the user wants to stress-test a plan against their project's language and documented decisions.

Compacts the current conversation into a handoff document another agent can pick up. Use when the user says 'handoff', 'hand off', or wants to continue this work in a fresh session.

Finds deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI

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

Analyze Python async code for correctness, patterns, and potential issues.

Profile Python code for performance bottlenecks using cProfile, memory_profiler, or py-spy.

Evaluate public API surfaces against guidelines and exemplars.

Principal-level architecture assessment against ADRs and design patterns.

Systematic bug detection with language-specific expertise.

Run a detailed review that picks its dimensions from what the codebase and diff contain.

Active security hardening of the existing codebase, with a report and concrete proposals to apply.

Audit Makefiles for best practices and portability.

Intensive mathematical analysis for numerical stability and correctness.

Static-analysis hot-spot review for time and space complexity.

Analyze code quality across 6 dimensions (duplication, algorithms, clean code, architecture, errors, style) and apply fixes.

Expert-level Rust audits for safety and correctness.

Audit shell scripts for correctness, safety, and portability.

View recent skill executions with full context and error details.

Analyze skill execution metrics and identify unstable or underperforming skills.

Evaluate and upgrade test suites with TDD/BDD rigor.

Run a computer use task on the desktop via Claude's vision and action API

Stage changes, generate conventional commit message, commit, and push to current branch. One-shot git add-commit-push.

Draft a Conventional Commit message for staged changes. Analyzes diffs, classifies change type, and formats scope/body.

Create git release tags from merged PRs or version args. Pushes a v-prefixed tag to trigger the release pipeline, then confirms the run started.

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.