LLM Mart Basic

Use when the user wants a cybernetic flow design document for an interactive system. Not for implementing or deploying the system.

Use when a user wants a looser conceptual graph for exploratory work. Not for remote, credential, publish, deploy, or irreversible changes.

Use when a human has an approved delivery plan and wants the full chain run under phase gates. Not for planning, open-ended debugging, or single-step execution: use work directly.

Use when the user runs /autoplan on a plan or idea. Reviews, amends, and derives task IDs with a final human approval gate. Not for remote, credential, publish, deploy, or irreversible changes.

Use when the user says release this, publish this package, or cut a release for a changesets-based npm package. Not for non-npm packages or releases without a changesets workflow.

Use when the user requests axiom, axiom-mode, axiom-compact, formal-logic, or compact form. Not for changing code or remote state.

Use when asked to park an undecided idea without representing it as decided or active work. Not for decided or active work: use the project task system.

Use when writing reset-to-main startup code, vector tables, VTOR, .data/.bss init, stack setup, startup.s, or crt0 for Cortex-M/RISC-V. Not for the bootloader jump: use bootloaders-embedded.

Use when writing Bazel BUILD files with cc_library or cc_binary rules, Bzlmod dependencies, toolchain registration, remote execution, sandbox debugging, or bazel query and cquery graphs.

Use when asked to validate a web app, CLI, API, or generated artifact against a source-blind behavior contract. Not for source or remote-system changes.

Use when building static archives with ar, stripping or converting binaries, mapping crash addresses with addr2line, or demangling C++ symbols. Not for ELF analysis: use elf-inspection.

Use when asked to determine what a change could break before it ships. Not for remote, credential, publish, deploy, or irreversible changes.

Use when the user names one book, course, paper, or source document and asks to distill it into a reusable skill. Not for a folder of sources: use map-corpus.

Use when writing a custom bootloader, jumping to application code, relocating VTOR, or implementing DFU/USB firmware update on Cortex-M. Not for reset-to-main: use baremetal-startup.

Use when C or C++ code needs memory-safety or undefined-behavior guarantees proved with CBMC, or ACSL contracts checked with Frama-C Eva or WP. Not for choosing the proof policy: use proof-driven.

Use when explaining branch predictors, mispredict penalties, speculative execution, Spectre or Meltdown mitigations, or branchless code. Not for pipeline stage theory: use cpu-pipelines-and-hazards.

Use when the user asks for branded or style-governed output. Not for remote, credential, publish, deploy, or irreversible changes.

Use when bloated code needs clean re-derivation, or the user says "this module is bloated" or "break it and rebuild". Not for untracked data or changes without VCS rollback.

Use when the user runs /browser-cookie-store to populate the session cookie store from installed browsers. Not for remote, credential, publish, deploy, or irreversible changes.

Use when the user runs /browser-qa for report-only QA results without entering a fix loop. Not for remote, credential, publish, deploy, or irreversible changes.

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

Generate requirements from goal and research

Run or re-run research phase for current spec

Smart entry point that detects if you need a new spec or should resume existing

Show all specs and their current status

Switch active spec

Generate implementation tasks from design

Decompose a large feature into multiple dependency-aware specs (epic triage)

Check for or install a verified Tree Ring Memory CLI update without changing installation scope

This directory contains the command implementations for the fast-agent CLI.

They operate it without you.

Promised, measured, accepted. A number nobody signed is claimed, not delivered.

Prepare the meeting. One page from the record.

Find the receipt. A dated line, or it did not happen.

Diagnose trust. Process gap, or they stopped trusting you.

Generate, convert, and maintain animated GitHub-safe Markdown documents with animated SVG diagrams. Covers four SVG patterns (architecture flow, lifecycle loop, field carousel, timeline phases), guided interview for any doc type (README, architecture guide, runbook, API reference, tutorial, RFC, post-mortem, how-it-works, or custom), converting existing plain Markdown, diffing for stale diagrams, quality auditing, local preview, and multi-platform export. Use when asked to "create a README for X", "write an architecture doc", "animate this guide", "convert my doc to animated", "check if my diagrams are stale", or "export my doc for Confluence".

AWS profile management for MCP servers — discover profiles across SSO, Granted, and assumed-role chains, check credential TTL, switch profiles across VS Code and Claude Code MCP configs, and scan AWS Organization accounts.

Structured guidance for AWS CloudFront distributions, WAF web ACLs, Lambda@Edge, CloudFront Functions, Firewall Manager multi-account enforcement, and IAM/IRSA patterns. Covers OAC, cache policies, security headers, managed rule groups, rate limiting, FMS FIRST/MIDDLE/LAST ownership model, and production-ready Terraform generation.

Azure identity (Workload Identity, OIDC, Entra ID), resource tagging, AKS platform patterns, RBAC scoping, and production-readiness review — with Terraform generation.

Design, run, and debug Chaos Engineering experiments on Kubernetes using Litmus Chaos v3 and Chaos Mesh v2. Covers fault injection (pod-delete, network-loss, CPU stress, node-drain), steady-state hypothesis probes, GameDay runbooks, scheduled experiments, DORA feedback loop, and RBAC setup. Use when asked to "inject a pod fault", "run a GameDay", "schedule chaos experiments", or "debug why my ChaosEngine is stuck".

Bootstrap Checkov on a developer laptop, run static or plan-level Terraform security scanning for AWS/Azure/GCP/EKS, resolve private GitHub modules via gh CLI, generate pre-commit hooks, produce multi-format output (cli/json/sarif/junit), and fix violations with AI-generated patches. Use when asked to "scan my Terraform", "run checkov", "check my IaC for security issues", "set up checkov pre-commit", or "fix checkov findings".

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.