LLM Mart Basic

Use when setting up or modifying CI/CD pipelines, quality gates, test runners, or deployment pipeline configuration through workflow files. Not for triggering a deployment.

Use when "CI is red", "fix the checks", or "make CI green", one check needs classifying, or a bounded sweep runs. Not for deploys, credentials, or rerun-as-fix. Non-CI bugs: use strike-the-root.

Use when a C or C++ build uses clang and needs diagnostics, optimization remarks, clang-tidy, ThinLTO with lld, LLVM PGO, or a GCC-to-Clang migration. Not for LLVM IR work: use llvm.

Use when setting up a project, auditing agent command permissions, or asking which read-only bash commands and domains to allow. Not for remote, credential, publish, deploy, or irreversible changes.

Use when the user just edited a durable artifact, or says "clean and true", "run the hygiene pass", or "taste the output". Routes the artifact through the hygiene passes it earned.

Use when asked to run /clean-clean-cut to cut accumulated records and residue. Not for untracked or non-VCS changes, or branch/worktree cleanup: use git-cleanup.

Use when asked to build or review a CLI intended for coding agents and return flag-driven, pipeline-safe, idempotent design advice. Not for running or profiling a CLI: use control-cli.

Use when the user wants to batch-close resolved or outdated tracker items. The agent never closes tracker items itself. Not for individual closure or items still under active work.

Use when a human explicitly runs /cloud-task-orchestrator for a large task across cloud agents to drain a verified task graph. Not for local subagent coordination: use orchestration-patterns.

Use when writing CMakeLists.txt, out-of-source builds, target_link_libraries, target properties, find_package/FetchContent, toolchain files, CPack, CMake presets, or cmake configure errors.

Use when reading llc output, tracing IR through legalization and instruction selection, or scoping a new LLVM target. Not for IR-level passes: use llvm-ir-and-passes.

Use when the user asks to simplify, clean, or refine code. Not for new abstractions or whole-codebase refactors.

Use when building or reusing a CodeQL database, running CodeQL security analysis, or modeling project-specific sources and sinks. Not for manual vulnerability review: use security-review (mode: confirmed).

Use when asked to commit changes, create a typed branch, format history for a changelog, or rewrite messages of HEAD or an unpushed range. Not for pushing or a PR: use commit-push-pr.

Use when a human asks to commit and push, not publish, the checked-out branch, including directly to the default branch, with no branch creation and no pull request. Not for a feature branch off the default: use commit-push-pr in its no-PR mode.

Use when asked to commit and push a feature branch, with or without a pull request. Its no-PR mode publishes without a PR. Not for a PR body alone: use create-pull-request.

Use when asked to research a feature across competitor products or to analyze competitor release changelogs (mode: changelog), and publish a cited report.

Use when the user asks for direction and a compilable 3D workflow from an interview. Not for remote, credential, publish, deploy, or irreversible changes.

Use when building a lexer, Pratt or recursive-descent parser, AST, symbol table, type checker, or LLVM IR emitter for a language or DSL. Not for optimizing IR: use llvm-passes.

Use when -O3 leaves a hot loop scalar, spills appear in assembly, or a PGO or BOLT deployment is planned or stalls. Not for machine lowering: use code-generation-and-backends.

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

Validate application configuration with schemas, per-environment rules, runtime checks, and secure handling of sensitive values

Preflight a DGX Spark system for an ML training or inference workload and emit env-report.json

Set up debugging and tracing with remote debugging, distributed tracing, debug logging, profiling, and production diagnostics

Generate API, architecture, code, and user documentation from a codebase and automate keeping it current

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Analyze and resolve errors across the full application lifecycle — from stack traces to distributed tracing — using systematic root-cause analysis and observability tools.

Set up error tracking and monitoring — implement structured logging, configure alerts, and integrate with error tracking services for real-time error detection.

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Generate comprehensive migration plans and scripts for transitioning codebases between frameworks, languages, versions, or platforms with minimal disruption.

Plan and execute safe, incremental dependency upgrades with minimal risk — including breaking-change migration paths and proper test verification.

Orchestrate legacy system modernization using the strangler fig pattern with gradual component replacement

Scaffold React and React Native components with TypeScript, tests, styles, and Storybook stories

Scan React, Vue, Angular, and vanilla JavaScript code for XSS vulnerabilities and report fixes with secure coding examples

Orchestrate end-to-end full-stack feature development across backend, frontend, database, and infrastructure layers

Orchestrate git workflow from code review through PR creation with quality gates

Create a role-specific onboarding plan for a new team member, from pre-arrival setup through the first 90 days

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Orchestrate multi-agent incident response with modern SRE practices for rapid resolution and learning

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…

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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.