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Found 9,065 Skills
Hand off the current task to the SLICC browser agent, or install a new skill into SLICC from a GitHub repo. Use this skill when the user says things like "handoff to slicc", "move this to slicc", "move to the browser", "test in the browser", "handoff to browser", "install this skill in slicc", "upskill slicc with this repo", "add this skill to slicc", or otherwise asks you to continue the work inside the SLICC browser agent.
Automated factory that converts GitHub repositories into standardized AI Skills. This tool is used when users provide a GitHub URL and want to "package", "wrap", or "create a Skill". It supports automatic retrieval of repository metadata, generation of standard directory structures, and injection of extended metadata required for lifecycle management.
Manage installation, version tracking, and update checks for Claude Code, Codex, and OpenClaw Skills. Supports installation from local paths or GitHub repositories, automatically identifies .codex/.claude/.openclaw target directories, records installation time, source URL, and version number for each Skill, and checks for GitHub updates.
Generate focused documentation for components, functions, APIs, and features. Use when creating inline docs, API references, user guides, or technical documentation.
When the user wants to build or improve a sales bot's ability to create handoff summaries and conversation notes. Also use when the user mentions "conversation summary," "handoff notes," "call notes," "CRM updates," or "conversation documentation."
Model Selection and Recommendation for Alibaba Cloud Tongyi Wanli. Activated when users need to "select, recommend, compare" models, or describe an AI scenario/functional requirement (implying the need to decide which model to use). The core intention is to help users make decisions, not just provide information. Trigger words: recommend model, which one to choose, which is suitable, compare, build a XX, implement XX function, which model is good to use, XX scenario solution. When users involve both model query and model selection at the same time, prioritize using this skill (this skill will read model data internally to complete the recommendation).
Operate SkipCalls AI phone receptionists through MCP. Use when the user mentions SkipCalls, AI receptionist/answering service/front desk, missed or inbound calls, call transcripts, scheduling a one-time outbound call, greetings, tasks, calendars, transfers, SMS behavior, business profile Q&A, or MCP connector setup.
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
Vote on or submit ideas for the frontpage.sh project pool. $0.01 USDC per action via MPP. Funded ideas pay back the suggester (50%) and voters (50% pro-rata).
Turn ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.
Translates an image (or a set of image references — screenshots, mockups, Figma URLs, live websites) into two mirrored design-system artifacts: `docs/design.md` (YAML tokens + prose, following Google's open [design.md](https://github.com/google-labs-code/design.md) format, for the coding agent) and `docs/design.html` (a self-contained, token-driven style guide rendering every token and component live, for the human to read). Reads the imagery, asks targeted clarifying questions, derives the design tokens (colors, typography, spacing, rounded, components), and writes both files. Fully standalone — requires no other document or skill. Use when the founder says "create a design system", "design from image", "translate image to design", "create design.md", "image to design system", "extract design tokens", or shares an image with no other clear intent.
Gary Vaynerchuk's jab-jab-jab-right-hook framework applied to a personal portfolio rotation on X and LinkedIn. Jabs = build-in-public + educational (value). Hooks = promo (the ask). Each property in the user's configured portfolio (see `~/.config/makerskills/jab-hook/properties.yaml`) gets a hook at least once every ~3 weeks; jabs fill the rest. Drafts go into the user's Typefully workspace via MCP. Modes — plan (7-day plan), pick-next (single post), audit (coverage report), draft (specific post). Triggers on "/jab-hook," "what should I post," "plan my socials," "next promo," "next jab," "next hook," "social rotation," "promote [property]," "BIP post," "audit my socials," "what haven't I posted about."