LLM Mart Basic

Use when the user asks for a weekly sentiment report, weekly social summary, or how mentions looked this week. Not for continuous monitoring or alerting.

Use when defining product strategy, starting or redirecting a product, or repairing stale STRATEGY.md. Not for project plans, roadmaps, scheduling, or work needing no interview.

Use when asked to find distribution opportunities for a template, tool, or artifact. Not for content creation or campaign management.

Use when a user asks for a product spec with invariants, a tech spec, or a PRD. Modes: product (default), technical, requirements. Not for task breakdown: use plan.

Use when asked to design or change a public API, route, CLI flag, or module boundary. Not for remote, credential, publish, deploy, or irreversible changes.

Use when non-trivial code needs a design, architecture needs improving, or one module needs targeted interface narrowing, seams, or testability. Not for diagrams, deploy, or irreversible changes.

Use when asked to run AST-based structural search, lint, or rewrite of code when regex is too fragile. 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 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 the user asks to simplify, clean, or refine code. Not for new abstractions or whole-codebase refactors.

Use when asked to implement under non-negotiable constraints: performance budgets, platform limits, legal or API rules. Not for remote, credential, publish, deploy, or irreversible changes.

Use when crossing a public API boundary, guarding complex invariants, or hardening untrusted input or integration seams. Not for remote or irreversible changes.

Use when asked to remove old code, migrate consumers, or decide whether to maintain or sunset a system. Not for untracked data or changes without VCS rollback.

Use when dependency upgrades need batching for CVEs, a major release, forced compatibility, a scheduled or vulnerability-triggered sweep. Not for PR queue triage: use github-backlog-triage.

Use when asked to design a module interface, seam, or testable boundary. Not for UI direction picking: use design. No source or remote-system changes.

Use when the user says deslop, debloat, tidy, simplify, clean a diff, or deslop branch diff, or remove dead code or config. Not for remote, credential, publish, deploy, or irreversible changes.

Use when code mixes units, fixed-point precisions, scaling factors, rates, prices, shares, or conversions. Not for type-level unit modeling: use type-driven.

Use when reconciling an API endpoint's generated OpenAPI schema and declared response types with its actual runtime response. Not for general API documentation: use docs-and-adrs.

Use when replacing a greenfield attempt with a clean pad of verified requirements. Not for rebuilding from primitives: use from-first-principle. Requires a committed, VCS-recoverable attempt.

Use when dead, duplicate, superseded, or generated residue must leave more than one artifact class of a repo or subsystem, preserving behavior. Not for one enumerated record set: use clean-clean-cut.

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

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging across Brazil, Mexico, Argentina, Colombia, Chile, an…

pi coding agent in a technicolor web trenchcoat

Open-source AI Search Intelligence Platform — track, analyze, and improve AI visibility, citations, prompts, competitors, and content opportunities across ChatG…

Open-source toolkit for the QVeris capability routing network: CLI, MCP server, Python SDK, skills, and REST API docs for agents to discover, inspect, call, and…

⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people w…

The AI agent that interacts with you in the real world.

Offline Codex Desktop migration for Windows and macOS.

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashbo…

Your smart, reliable, and friendly personal AI assistant.

The LLM Anti-Framework

A general-purpose AIGC video engine: script to finished film in one pipeline — dramas, ads, product videos, otome games, and more. | 通用 AIGC 视频引擎 —— 从剧本到成片一条流水线…

GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

DeepSeek Harness (dsh) Windows desktop client - bundled Node.js + dsh CLI, one-click launch

Open-source, real-time collaborative AI canvas - notes, mini-apps, and agents on one infinite board.

MCPSafari: Native Safari MCP Server for AI Agents

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Po…

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, with…

Ouroboros — self-creating AI agent. Born Feb 16, 2026.