M4NUSH7
UserBattle-tested Claude Code & Cowork skills that double your usage, same quality.
Categories
Indexed Skills (9)
ponytail
Forces the laziest solution that actually works - simplest, shortest, most minimal. Channels a senior dev: question whether the task needs to exist (YAGNI), reach for the standard library before custom code, native features before dependencies, one line before fifty. Intensity levels: lite, full (default), ultra. Use on ANY coding task - writing, refactoring, fixing, reviewing, or designing code, and choosing libraries. Also whenever the user says "ponytail", "be lazy", "lazy mode", "simplest/minimal solution", "yagni", "do less", "shortest path", or complains about over-engineering, bloat, or boilerplate. Covers bundled subcommands: /ponytail-review (diff - "what can we delete"); /ponytail-audit (whole-repo - "find bloat"); /ponytail-debt ("what did ponytail defer"); /ponytail-gain (scoreboard); /ponytail-help. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).
scrapling
Scrape web pages using Scrapling with anti-bot bypass (like Cloudflare Turnstile), stealth headless browsing, spiders framework, adaptive scraping, and JavaScript rendering. Use when asked to scrape, crawl, or extract data from websites; web_fetch fails; the site has anti-bot protections; write Python code to scrape/crawl; or write spiders.
agent-reach
Use when the user wants to research a topic, find sources, or search a platform by name - web pages, YouTube, GitHub, RSS/Atom feeds, V2EX, or Exa semantic search. Also when the user shares a URL from one of these platforms and wants it read, summarized, or checked for related content. Routes each request to the right zero-config CLI/API (curl+Jina Reader, yt-dlp, gh, feedparser, mcporter+Exa, V2EX) so results come back as raw source material, not narrowed by one search engine. Pairs with deep-research: use agent-reach first to gather from multiple platforms, then hand the material to deep-research (or synthesize yourself). NOT for: writing the final report/analysis/translation (it only fetches/searches); posting, commenting, or any write action; Twitter/X, Reddit, Facebook, Instagram, LinkedIn, XiaoHongShu, Xueqiu, or Bilibili unless cookies or a login session are already set up (see "Key/cookie-gated channels") - confirm setup first.
graphify
Use for codebase comprehension - navigating an unfamiliar or large repo, understanding how code connects, building a call/import graph, answering "where is X used" or "what calls Y", or tracing a path between two functions/modules - instead of blind grep+read loops that re-read the same files every turn. Builds a queryable code graph once (graphify update), then answers via graphify query/path/explain against that graph. Not an agent orchestration engine (it maps CODE structure, not agent workflows); not for web scraping or general data collection.
init-harness
One-shot initialization of a parallel-terminal Claude Code build harness in a project - phase checkboxes as the task queue, pinned model/effort per agent, mechanical git-tag gates, hardened read/gate/log hooks, Obsidian memory vault plus SQLite agent memory, human-gated pivots, and CI drift checks. Use when the user says "/init-harness", "init-harness", "initialize the harness", "set up the build harness", "scaffold this project's harness", "bootstrap the agent harness", or drops in a project-context.yml and asks to initialize. Also use when a project needs multi-terminal agent orchestration with gates, or when an existing harness must be verified/repaired (hooks not firing, guards not blocking, .agents drift). Do NOT use for adding a single agent or skill to an existing project.
token-efficiency
Comprehensive token optimization: RTK (Rust Token Killer) command-output compression, efficient file/command strategies, hard model-routing rules (Sonnet 4.6 coders, Opus 4.6 orchestrator, Haiku 4.5 logging), Source-of-Truth keyword framework, hybrid SQLite agent memory with checkpoints, and concise output style. Use this skill whenever running dev CLI commands (git, cargo, npm, pytest, docker), spawning coding subagents, writing logs or agent memory, setting up a project's keyword index, checkpointing, or whenever the user mentions 'rtk', 'token efficiency', 'token savings', 'context bloat', 'model routing', 'checkpoint', 'agent memory', or 'source of truth'. Also use to install/verify RTK or its Claude Code hook.
ui-standout
Pick STANDOUT, fit-for-purpose UI components per use-case instead of reusing the same mundane flows. A 3-layer method: query real component catalogs (astryx / shadcn / Aceternity) for candidates, reject AI-slop defaults with a 46-rule taste gate (harvested from impeccable), and justify the pick with design principles (hierarchy, spacing, type, color, Von Restorff standout). Ships a use-case -> component map so a checkout, dashboard, hero, onboarding, or empty-state screen gets a standout component, not a stock grid. Use this BEFORE building or choosing any UI component, screen, page, layout, form, or design system; when the user says a UI is bland/generic/mundane/"looks like every other app" and wants it to stand out; when scaffolding the Presentation layer of a web/SSR/static app; or when reviewing a built UI for slop. Not for backend/serverless-API/networking services (no UI) - and not for charts specifically (the dataviz skill owns those).
install-skill
End-to-end skill package installer and builder for Claude. Handles the FULL process: platform targeting (CLI / CLI+Desktop / Desktop), acquiring complete packages from GitHub repos or local folders (never just SKILL.md - all references, scripts, hooks, binaries, templates), relevance selection, personalization, platform adaptation, verification, packaging (.skill zips, staged folders), and install commands. Use this skill whenever the user wants to install a skill, install a skill package, add a skill from a repo or URL, build a skill package, port a skill between CLI and desktop, combine skills, or repackage/update an installed skill. Also use when the user complains a previous install only grabbed SKILL.md.
skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.