LLM Mart Basic

Go-to-market strategy planner. Generates a complete GTM plan across paid, unpaid, marketing, sales, and AI-automation channels for any project — and hands executable campaigns off to /marketing.

Full inbox management across all channels — WhatsApp (wacli), Email (Gmail MCP), Slack (MCP), Telegram (user-auth MCP), Discord (webhook + REST read), Notion (MCP — comments, mentions, assigned tasks). Scans FULL inbox (not just unread), identifies messages needing replies, archi

Add any SaaS API as a first-class integration. Provide the service name — ops-integrate discovers auth patterns, tests connectivity, and registers the API in your partner registry so it's available to other skills.

Linear command center. Shows current sprint, creates/updates issues, manages priorities, syncs with GSD phases.

Marketing command center. Email campaigns (Klaviyo), paid ads (Meta/Google), analytics (GA4), SEO, and social media metrics. One dashboard for all marketing channels.

Autonomous PR merge pipeline. Scans all repos for open PRs, dispatches subagents to fix CI, resolve conflicts, address review comments, then merges. Use --main to also sync dev↔main branches.

Unified APM and monitoring surface. Polls Datadog, New Relic, and OpenTelemetry backends for active alerts, error traces, and entity health. Use --watch for live polling every 60 seconds. Use --setup to configure monitoring credentials.

Business-level "what should I do next". Priority stack — fires > unread comms > ready-to-merge PRs > Linear sprint > revenue-generating GSD work. Uses pre-gathered data and routes to the right skill.

Autonomous multi-project orchestration engine. Audits all registered projects, structures work into dependency-wired tasks, dispatches parallel agents (subagents or Agent Teams), audits completions, and ships PRs. Registry-driven — works for any user with a configured project reg

Ship parcels via any configured carrier — MyParcel, Sendcloud, DHL Parcel NL, PostNL, DPD, UPS, FedEx. Auto-selects the first carrier whose credentials are configured, or pass --carrier <name> to override. Verbs: ship, label, track, list, carriers.

Portfolio dashboard for all GSD-tracked projects. Scans ~/Projects and ~/gsd-workspaces for .planning/ directories, shows phase status, git state, blockers, and next actions for every project. Run /ops projects to see the full portfolio.

Revenue and costs tracker. AWS spend via aws ce, credits tracker, project revenue stages. Shows burn rate, runway estimate, credits expiring.

Post-setup credential manager. Shows current integration status (configured/missing/expired) and lets you update individual credentials without re-running the full setup wizard. Runs a smoke test after each update.

Cross-platform, hardware-adaptive system optimizer. Auto-detects macOS / Linux / WSL / Windows (MINGW/Cygwin/MSYS2) and CPU/RAM/disk/GPU profile, then picks the right cleanup strategy. Scans reclaimable disk space, memory pressure, runaway processes, startup bloat, network issues

Lightweight green/red status panel for every configured integration. No gather, no actions.

Cross-platform issue triage. Pulls from Sentry (MCP), Linear (MCP), GitHub Issues (gh). Cross-references against code to find already-fixed issues. Auto-resolves fixed ones. Dispatches agents for active issues.

Voice operations — make phone calls (Bland AI), text-to-speech (ElevenLabs), transcribe audio (Whisper/Groq). Replace OpenClaw voice capabilities.

WhatsApp Business Cloud API — send approved template messages at scale, manage templates with approval tracking, and integrate product catalogs. Separate from wacli personal WhatsApp.

YOLO mode. Spawns 4 parallel C-suite agents (CEO, CTO, CFO, COO). Each analyzes the business from their perspective using ALL available data. Produces unfiltered Hard Truths report. After user types YOLO, autonomously runs the business for a day using /loop.

Completely remove claude-ops plugin, all stored credentials, cached files, shell exports, and MCP registrations. Confirms each step before deletion.

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

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.

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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.

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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.