LLM Mart Basic

Use when the user wants to lint a repo following the Karpathy LLM Wiki pattern (raw/ + wiki/ + SCHEMA.md / index.md / log.md). The skill detects path, scans wiki pages + schema layer, reports frontmatter gaps, broken in-body links, source traceability breaks, stale claims, orphan

Use when the user wants to turn a Markdown report into a presentation-quality .pptx via interactive design decisions and a reusable hand-coded build script. Drives pre-analysis, global style choices, optional per-slide layout dialogue, python-pptx composition, and optional LibreO

Use when the user wants to lint a Claude Code memory directory (~/.claude/memory or custom path) for index inconsistency, broken cross-links, stale project state, duplicate / conflicting feedback rules, naming violations, frontmatter gaps, and oversized files. Phase 1 is a read-o

Use when user wants to break a PRD into Azure DevOps work items via vertical-slice plan. Workflow: read PRD → quiz user to lock durable decisions → draft slices with HITL/AFK + blocked_by → call az CLI directly via Bash to create items + Predecessor relations. Idempotent re-runs

Use when user wants to draft a PRD (Product Requirements Document) from raw input (meeting transcripts, hand-waved descriptions, scattered decisions). Workflow: load org's PRD Guideline + writing discipline → lock execution mode (human-run vs unattended-agent-run) → ingest raw in

Prepare an existing project for GitHub or public release with scope-appropriate checks for sensitive data, documentation, installation, tests and release artifacts. Separate release blockers from polish, preserve existing authorization, and verify the published result only when p

Use when the user wants to evaluate a GitHub repository before installing, running, forking, or depending on it. Takes a GitHub repo URL, cleans tracking params, shallow-clones to /tmp, inspects dependency/supply-chain risk, static vulnerability patterns, issue-reported security

Use when the user wants to rewrite Markdown prose into a conversational, humorous, self-deprecating engineering tone while preserving technical accuracy and document structure. Rewrites prose sections only, keeps code blocks, diagrams, tables, English summary blocks, and factual

Use when the user wants a Traditional Chinese (Taiwan) language review of Markdown or plain-text files — flagging genuinely comprehension-breaking grammar faults (missing subject, broken predicate, wrong measure word, misused connectives, inconsistent naming) and non-Taiwanese wo

Use when the user wants privacy-respecting web, image, news, or video search through a configured local SearXNG instance instead of external search APIs. Calls the bundled script against SEARXNG_URL, supports result limits/categories/language/time range, and can return human-read

Use when the user wants to register, inspect, manually run, or remove scheduled Claude skills with Telegram push notifications. Presents a menu, discovers schedulable skills with headless-prompt frontmatter, converts natural-language schedules into cron entries with conflict conf

Use when the user is unsure which kc_ai_skills workflow skill to use, or describes work involving PRD, SD/software design, FR, AC/acceptance criteria, ADR, tickets, implementation, debugging, existing-project documentation, release checks, or unattended agent execution. Triage th

Use ONLY when the user's latest message explicitly contains the `/wrap-up` command. Harvests everything a long session produced into the project following that project's own rules — moves stray media in, wires two-way refs, updates indexes, merges drafts into SSOT — then dispatch

The single source for all API budget cap and reset rules - how much of the 5-hour and weekly API limits may be spent, when to throttle, pause, wake up, or hibernate, and the commit-identity gate that runs before any commit. Use whenever you are about to start or continue autonomo

Secure everything the user approved before a context compaction so a later /compact can never lose or alter it. Writes verbatim intent and handoff state to disk and commits plus pushes the tracked work product in the correct repository, then reports whether it is safe to compact.

Detect when a concern is scattered across many places in a project (config keys, enums, translations, feature flags, API endpoints, doc references) and auto-generate a project-local checklist so that same concern is never partially updated again. Use whenever you add or change so

Read-only root-cause diagnosis for a symptom, bug, failure, or unexpected behavior. Establishes the mechanism at file:line and reads up the facts instead of guessing, before any fix is attempted. Produces a diagnosis report; the fix is always a separate step gated by an explicit

Disable credo for the current directory. Use when the user wants to stop credo here - for example "stop using credo here", "disable credo for this repo", "turn credo off here", "no credo in this directory", "credo hier aus", "credo hier deaktivieren", "credo hier abschalten" - or

Enable credo for the current directory. Use when the user wants credo active here - for example "enable credo here", "use credo here", "turn credo on here", "credo hier an", "credo hier aktivieren", "credo hier einschalten" - or runs the /credo:enable command. It persists a per-d

Explain something in depth on request. Use when the user writes "???" - alone, or placed directly after a reference, statement, or term - which means "explain that in more detail, with a concrete example AND consequences". Also invoked by the /credo:explain command. Treat the poi

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.

Run an ad-hoc ordered chain of pm-skills with shared context (ephemeral; routes to the pm-workflow-orchestrator)

Run the Customer Discovery workflow (research -> JTBD -> opportunities -> problem)

Run the Design Sprint workflow (5-day prototype-and-test arc producing a Decider's build/iterate/pivot/stop call)

Run the Feature Kickoff workflow (problem -> hypothesis -> PRD -> stories)

Run the Foundation Sprint workflow (2-day strategic-alignment arc producing a Founding Hypothesis)

Run the end-to-end Foundation Sprint + Design Sprint workflow with narrative handoff

Run the Post-Launch Learning workflow (instrumentation -> dashboard -> results -> retro -> lessons)

Run the Product Strategy workflow (competitive analysis -> stakeholders -> opportunities -> solution -> ADR)

Run the Sprint Planning workflow (refinement -> stories -> edge cases)

Run the Stakeholder Alignment workflow (stakeholders -> problem -> solution -> launch)

Run the Technical Discovery workflow (spike -> ADR -> design rationale)

Placeholder command file for the WS-T9 dual-shell parity smoke. No count phrases.

Fast non-interactive briefing before any meeting — auto-detects your next calendar event, pulls relationship history, surfaces open commitments, and produces a one-page brief in under 30 seconds. Use this whenever the user says "brief me", "give me a quick brief", "what's coming up", "background on my next call", "who am I meeting next", "brief me on Sarah", "I have a call in 10 min", "quick rundown", or right before walking into a meeting. Different from /minutes-prep — brief is the fast hook-fireable version that doesn't ask questions and doesn't set goals. Use brief when speed matters; use prep when the user wants to think hard about goals first.

Manage old recordings — find large files, archive old meetings, delete processed originals. Use when the user says "clean up recordings", "how much space are meetings using", "delete old recordings", "archive meetings", "manage meeting storage", or asks about disk space from minutes.

Start and control Minutes Coach, the separate real-time copilot HUD, with an explicit meeting goal. Use only for explicit Coach or HUD lifecycle requests such as "start Minutes Coach", "open the Coach HUD", "pause Minutes Coach", "resume Minutes Coach", "Minutes Coach status", or "stop Minutes Coach". Do not use for requests that explicitly ask the current terminal agent to watch or strategize; those belong to minutes-live-sidekick. An ambiguous request such as "coach me live" requires one short surface clarification and must not automatically start Coach.

Post-meeting debrief — analyzes what happened, compares outcomes to your prep intentions, tracks decision evolution. Use when the user says "debrief", "what just happened in that meeting", "what did we decide", "debrief that call", "post-meeting", "what changed", or right after stopping a recording.

Policy-safe relationship rankings, commitments, aliases, person profiles, and topic research. Always use Minutes' bounded native CLI surfaces; never build or read a durable graph cache.

Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.

Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation data.

Health-check your meeting knowledge for contradictions, stale commitments, and decision conflicts. Use when the user asks "any conflicts in my meetings", "check for stale action items", "lint my meetings", "consistency check", "are there contradictions", or wants to audit their decision history.

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.