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Claude Skills by FAIRY123456789
github.com/FAIRY12345678918 skills0 installs32 views
- Build In Public LauncherTurn a finished or nearly finished Skill, plugin, repository, micro-tool, research utility, or AI project into a credible public launch that can earn real users and feedback. Use when the work exists but nobody outside the creator has tried it, the README is weak, the launch has no demo or proof metric, or the user wants a GitHub-first build-in-public plan without fake traction or vanity metrics.Votes: 0GitHub stars: 96
- Skill From ScarsMine repeated pain from transcripts, project retrospectives, debugging logs, failed prompts, deployment notes, or work history and decide whether it deserves to become a reusable Agent Skill. Use when the user wants to turn hard-earned experience into open-source knowledge, avoid publishing generic prompts, generate a SKILL.md package with references and evaluations, or identify which repeated mistakes contain a real decision procedure worth sharing.Votes: 0GitHub stars: 96
- Vibe To SpecConvert messy voice input, imperfect speech recognition, half-formed product ideas, and iterative corrections into an implementation-ready software specification for Codex, Claude Code, Copilot, Cursor, or another coding agent. Use when the user speaks faster than they structure requirements, named entities are misrecognized, context or memory can safely resolve recurring terms, and the final output needs scope, flows, data, constraints, acceptance tests, and explicit unknowns rather than a r...Votes: 0GitHub stars: 96
- Voice Dump To TodoConvert a long, messy, repetitive, speech-recognition-heavy task dump into a precise executable to-do list. Use when the user speaks tasks in inaccurate ASR language, changes priorities mid-sentence, mixes ideas with actions, or wants a downloadable standalone interactive HTML to-do that can be saved or dragged to the desktop. Use context-aware named-entity repair when a recurring term is clearly misrecognized, preserve uncertain corrections, and produce concrete definitions of done.Votes: 0GitHub stars: 96
- Voice With TemperatureRewrite, edit, or draft prose so it becomes clearer while retaining the writer's lived detail, emotional temperature, uncertainty, rhythm, specificity, and intellectual character. Use for reflections, personal essays, technical writing, speeches, bios, posts, or formal prose when normal AI polishing makes the text generic, over-smoothed, slogan-like, or emotionally fake.Votes: 0GitHub stars: 96
- Aliyun Fullstack DeployDeploy full-stack apps to user-authorized Alibaba Cloud ECS or comparable Linux VPS hosts with preflight, canary verification, and rollback. Use for production deployment and recovery; never purchase infrastructure or mutate an unauthorized host.Votes: 0GitHub stars: 96
- Anti Slop Personal BrandAudit a resume, GitHub profile, personal website, portfolio, bio, README, or project list for generic AI slop, stale student-project signals, unsupported grand claims, fragmented identity, weak proof, and outdated first-screen positioning. Use when the user wants a personal brand that feels current, specific, technically credible, and earned rather than over-designed or stuffed with fashionable keywords.Votes: 0GitHub stars: 96
- Cross Domain TranslatorTranslate a problem, workflow, or project from one professional domain into another while preserving the real structure. Use when someone needs to connect domain expertise with software, AI, product, research, data, policy, operations, or another field. Rebuild actors, objects, states, events, constraints, evidence, metrics, and failure modes instead of merely replacing vocabulary.Votes: 0GitHub stars: 96
- Csdn Technical WritingDraft, rewrite, or audit Chinese CSDN-style technical articles using a specific long-form teaching structure: a plain-text overall title, Markdown headings for section levels, dense natural paragraphs, beginner-first progression, commented code examples, and splitting when an article becomes too long. Use for technical tutorials, AI and backend articles, engineering practice notes, and beginner-friendly series.Votes: 0GitHub stars: 96
- Deep Talk To PodcastTransform a long private conversation, voice transcript, mentor chat, interview, or two-person deep talk into a privacy-aware podcast package: the real turning points, a natural two-host or interview-style script, show notes, title options, short clips, and a current AI-audio platform recommendation. Use when a normal summary would lose the chemistry and reasoning, or when the user wants to turn a meaningful conversation into a listenable private or public audio artifact.Votes: 0GitHub stars: 96
- Deployment ProofConvert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets. Use after a software deployment, migration, recovery, or automation project when the user wants to demonstrate learning ability or impact without leaking host identities, credentials, private paths, customer data, or invented metrics. Do not publish or push unless the user explicitly asks.Votes: 0GitHub stars: 96
- Fitness Recovery CoachBuild practical training, recovery, and habit plans from a user's goal, training age, schedule, equipment, sleep, fatigue, pain signals, and current routine. Use for beginner fitness planning, strength or hypertrophy routines, fat-loss habits, recovery-day adjustments, low-risk return-to-training decisions, and training logs. Do not diagnose injuries or replace medical care.Votes: 0GitHub stars: 96
- One Week Founder ModeCompress an overloaded week of startup, research, job-search, creator, or side-project work into one main bet, up to two microbets, essential maintenance, and an explicit kill list. Use when the user has too many parallel ideas, keeps adding tasks, needs a founder-like weekly operating rhythm, or wants every week to end with real external proof instead of a long completed-task list.Votes: 0GitHub stars: 96
- Personal BoardroomStress-test a difficult career, startup, study, money, product, or life decision through a small board of explicit decision lenses, then synthesize one evidence-weighted recommendation. Use when the user is torn between options, has several identities or goals in conflict, keeps receiving contradictory advice, or wants more than a generic trade-off list.Votes: 0GitHub stars: 96
- Small Server FitAssess whether a web application and its build and runtime plan fit a low-cost Linux VPS or Alibaba Cloud ECS before purchase, implementation, or deployment. Use when choosing an OS image, Python, Node.js, or Java versions, build location, worker count, swap strategy, or minimum CPU, RAM, and disk for a repository. Produce evidence-backed FIT, FIT WITH CHANGES, NOT FIT, or NOT MEASURED decisions; do not recommend purchasing from guessed capacity.Votes: 0GitHub stars: 96
- Social Signal And TactRead relationship signals across a conversation, infer what changed between turns, then turn awkward, overly formal, blunt, or AI-sounding messages to teachers, leaders, mentors, senior colleagues, partners, acquaintances, or potential professional contacts into short, natural, relationship-aware communication. Use for tactful praise, upward communication, progress updates, favors, reminders, apologies, disagreement, gift and courtesy messages, proxy greetings, holiday wishes, warm friend-lik...Votes: 0GitHub stars: 96
- Student Money Four BucketsHelp university students allocate a common monthly living allowance into four practical layers: essentials, uncertainty buffer, long-term reserve and growth, and deliberate non-essential enjoyment. Use for budgeting, overspending diagnosis, monthly allowance planning, saving goals, or deciding how much can be safely spent on entertainment without pretending student life should contain zero fun. Do not use it for personalized investment selection.Votes: 0GitHub stars: 96
- Trend To MicrobetTurn a fast-moving AI, product, creator, career, or technology trend into a small evidence-producing bet instead of a vague FOMO reaction. Use when the user says something is suddenly hot, wonders whether to chase a new model, platform, agent, Skill, or plugin, or wants a 48-hour to 7-day experiment with a clear upside, effort cap, proof metric, and stop rule.Votes: 0GitHub stars: 96