LLM Mart Basic

Create irresistible offers using the Value Equation, bonus stacking, risk-reversing guarantees, and ethical scarcity. Use when the user mentions "grand slam offer", "make my offer more compelling", "what bonuses should I add", "guarantee strategy", "offer naming", or "people say

Guided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinter

Guided journey from a stalled, plateaued business to one with an honest diagnosis, a working operating rhythm, and offers repriced to real value. Orchestrates eight skills phase by phase - good-strategy-bad-strategy, traction-eos, high-output-management, team-topologies, drive-mo

Guided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, sof

Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users sign up but dont stick around", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", or "aha moment". Also trigger when anal

Guided journey from a live website that underperforms to a prioritized, evidence-backed backlog of conversion, usability, message, and speed fixes - each shipped as a testable experiment. Orchestrates eight skills phase by phase - cro-methodology, ux-heuristics, refactoring-ui, w

Apply the seven principles of ethical persuasion (reciprocity, commitment, social proof, authority, liking, scarcity, unity) to product design, copy, and sales. Use when the user mentions "social proof", "persuasive copy", "why users dont convert", "ethical persuasion", "reciproc

Build empowered product teams using discovery and delivery dual-track. Use when the user mentions "product discovery", "empowered teams", "feature factory", "opportunity assessment", "product vision", "product strategy", "what should we build", or "our roadmap is just a feature l

Design native iOS interfaces following Apple Human Interface Guidelines. Use when the user mentions "iPhone app", "iPad layout", "SwiftUI", "UIKit", "Dynamic Island", "safe areas", "HIG compliance", "SF Symbols", "haptic feedback", "iOS accessibility", "make my app feel native",

Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or

Choose and audit startup metrics using Croll and Yoskovitz's "Lean Analytics". Use when the user mentions "what metrics should we track", "KPIs", "north star metric", "One Metric That Matters (OMTM)", "vanity metrics", "analytics dashboard", "DAU/MAU", "churn benchmark", or "meas

Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation accounting", "build-measure-learn", "mini

Apply lean thinking to UX: hypothesis-driven design, collaborative sketching, and rapid experiments instead of heavy deliverables. Use when the user mentions "Lean UX", "design hypothesis", "outcome over output", "design studio method", "assumption mapping", "lightweight research

Craft messages that are understood, remembered, and drive action using the SUCCESs checklist (Simple, Unexpected, Concrete, Credible, Emotional, Stories). Use when the user mentions "make it memorable", "no one remembers our pitch", "tagline", "value proposition", "why the messag

Design the small details -- triggers, rules, feedback, loops and modes -- that separate good products from great ones. Use when the user mentions "microinteraction", "button feedback", "loading state", "toggle design", "animation detail", "state transitions", "input feedback", "t

Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but dont buy", "leading questions", "The Mo

Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation". Use when the user mentions "pricing", "how much should we charge", "willingness to pay", "pricing page", "packaging", "freemium vs free trial", "are we leaving money

Prepare and execute negotiations using tactical empathy, calibrated questions, and the Ackerman method. Use when the user mentions "salary negotiation", "contract terms", "handling objections", "mirroring and labeling", "difficult conversation", "deal terms", "BATNA", "anchoring"

Define product positioning by mapping competitive alternatives, unique attributes, and best-fit customers to the right market category. Use when the user mentions "positioning", "competitive alternatives", "how to position", "market category", "positioning canvas", "repositioning

Build a complete marketing plan covering the full customer journey from stranger to raving fan. Use when the user mentions "marketing plan", "marketing strategy", "target market", "USP", "lead nurture", "customer lifetime value", "PVP Index", or "I dont know where to start with m

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.

Instrument services with structured logging, Prometheus metrics, and OpenTelemetry tracing. Build Grafana dashboards, write Prometheus alerting rules, run k6 load tests, and plan infrastructure capacity.

Generate, test, validate, explain, and debug OPA (Open Policy Agent) Rego policies and Conftest configurations. Covers deny/warn/violation rules, unit tests, regal linting, conftest fmt, namespace design, input shape analysis, and GitHub Actions integration. Use when asked to "write a policy", "test a rego file", "validate policies", "explain this rego", or "why is my policy not firing".

OpenShift SCC diagnosis and hardening, Route TLS patterns, OpenShift GitOps app delivery, and cluster upgrade validation.

Comprehensive PR review across six dimensions — cost impact, environment drift, ownership gaps, SOC 2 compliance, deprecated API / version hygiene, and rollback feasibility. Each mode inspects the diff and current file state, reports findings with severity, and recommends concrete fixes. Use when preparing a PR for merge, conducting a pre-deployment readiness check, or performing a post-merge risk assessment.

Production-readiness preflight check for a directory, repo, or single file. Auto-detects file types (Kubernetes manifests, Terraform, GitHub Actions workflows, Helm values/charts, Flux Kustomizations/HelmReleases, Dockerfiles, shell scripts) and applies type-specific checks across the whole scope. Returns a per-file summary table and aggregated verdict. Use before deploying, merging, or applying a folder of config. For PR diffs spanning multiple files use /platform-skills:pr-review instead. For deep Helm chart work use /platform-skills:helmchart instead.

Apply product thinking to platform work — DevEx audits, friction analysis, RFC/ADR drafting, incident communication, post-mortems, capacity planning, cost optimisation, and platform health review.

Generate renovate.json covering all dependency file types used in a repo, emit a GitHub Actions workflow that validates renovate.json on every PR, or generate a pre-commit hook for local validation.

Detect and respond to in-container threats at the syscall level using Falco (eBPF-based, CNCF, open-source, no license cost). Covers Falco installation on EKS/GKE with eBPF driver, custom rule authoring, alert routing via Falcosidekick, rule debugging, and bridging Falco runtime signals to Kyverno admission enforcement. Use when asked to "detect privilege escalation in containers", "set up runtime threat detection", "write a Falco rule", "route Falco alerts to Slack", or "debug why my Falco rule is not firing".

Secrets strategy, External Secrets Operator scaffolding, Sealed Secrets seal/rotate/backup, rotation runbooks, and Kubernetes-side secrets audit.

Bootstrap and operate a self-improving agent workspace. Scaffolds .learnings/ and memory/ directories, captures errors and learnings during a session, detects recurring patterns, recalls verified lessons, and promotes stable entries to scoped rule files (.claude/rules/ or ~/.claude/rules/). Also implements the Proactive Agent pillars — WAL protocol, working buffer, SESSION-STATE, daily notes, VBR, VFM scoring, ADL decision logic, heartbeat, and reverse prompting. Use when asked to "remember this lesson", "set up agent memory", "log that error", "what did we learn about X", "promote learnings", "revoke that rule", "capture session state", or "enable proactive mode".

Scaffold a multi-agent AI setup for any repo. Scans the codebase, interviews the developer, generates agent configs for whichever AI tools the repo uses (Copilot, Claude Code, Cursor, Codex, Windsurf). Use when asked to "set up agents", "scaffold Copilot agents", or "create an AGENTS.md".

Secure the software supply chain from source to running container. Covers Cosign keyless image signing (Sigstore/Rekor), SBOM generation and attestation (Syft), vulnerability scanning with severity gates (Trivy/Grype), SLSA Level 2 provenance, and Kyverno/OPA admission enforcement. All open-source, no license cost. Use when asked to "sign my image", "generate an SBOM", "scan for CVEs", "attest build provenance", "enforce image signatures in Kubernetes", or "implement SLSA".

Runs through the full Terraform validation pipeline — fmt, validate, tflint, security scan — and reviews a module or plan for blast radius, IAM risk, and state impact.

Triages a PR comment — from a bot (Copilot, CI) or a human reviewer. Routes to the `triage_helper.py` helper for identity checks, thread snapshotting, isolated-worktree fixes, and publish/reply/resolve mechanics; you classify the finding and apply a justified fix. `--dry-run` is fully read-only (investigation and a printed plan, zero mutations). `--no-resolve` runs the full fix/reply workflow but never resolves a thread. Run from inside the repo.

Scan container images, filesystems, git repos, and existing SBOMs for CVEs, secrets, and license violations using Trivy. Covers local CLI, CI severity gates with SARIF upload, and continuous monitoring via Trivy Operator (Flux HelmRelease). Use when asked to "scan my image", "check for CVEs", "scan this repo for secrets", "scan an SBOM", or "set up continuous cluster vulnerability monitoring". IaC misconfig → /platform-skills:checkov. Admission posture → /platform-skills:kyverno. Image signing/SBOM generation → /platform-skills:supply-chain.

Audit GitHub Actions workflows, composite actions, Dependabot configs, and pre-commit configs for security findings using zizmor — template injection, credential persistence, unpinned uses, over-broad permissions, impostor commits. Covers local CLI, auto-fix, zizmor.yml policy, severity-based CI gates, SARIF upload, and pre-commit. Use when asked to "audit my workflows", "run zizmor", "is this workflow safe", "check for template injection", "pin my actions", or "set up a zizmor CI gate". Workflow syntax and shell errors → /platform-skills:github-actions (actionlint). IaC misconfig → /platform-skills:checkov. Image and dependency CVEs → /platform-skills:trivy. Keeping SHA pins fresh → /platform-skills:renovate.

반복 작업을 `/이름` 으로 호출. 파일명 = 커맨드 이름(`fix-issue.md` → `/fix-issue`).

이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):

AGENTS.md 생태계(rules·memory·agents·skills·commands·workflows)의 연결 구조를

이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→PR/MR)을 사람 개입 없이 자동 실행.

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.