Product & Planning

ivanshamaev Skill

StarRocks cluster health monitoring — FE/BE/CN node status, tablet health, replica status, compaction backlog, storage imbalance, SHOW commands, system tables (information_schema/sys), alert thresholds, FE quorum checks, BE disk usage, dead replica detection, Prometheus metrics

ivanshamaev Skill

DataOps blameless postmortem generation — severity matrix (SEV1-4), postmortem Markdown template with timeline/impact/root cause/action items, 3 filled-in examples (Kafka rebalance/dbt incremental data loss/ClickHouse schema mutation), CAPA framework (Corrective/Action/Preventive/Action), impact quantification SQL, stakeholder communication templates, 60-min facilitation guide, postmortem review checklist, Git-based postmortem repository management

taipt1504 Bundle

Foundation skill — auto-loads at SessionStart. Teaches 5-layer adaptive workflow, 1% pre-flight discovery rule, triage routing, skill announcement contract, project detection. All other skills depend on this. Do NOT manually load.

taipt1504 Bundle

Mandatory pre-flight discovery before every workflow gate. Enumerate ALL skills + rules ≥1% relevant. Justify every SKIP with concrete evidence. Produces artifact downstream gates + subagents consume. Meta-skill — fires before all other skills.

ivanshamaev Skill

DataHub data catalog — metadata ingestion recipes (PostgreSQL/Hive/Spark/dbt/Airflow/Kafka/S3), Python SDK (DatahubRestEmitter, MetadataChangeProposalWrapper), column-level lineage (FineGrainedLineage), GMS/MCE/MCP architecture, Kubernetes Helm deployment, CLI operations, search/discovery REST API and GraphQL

wooyoohl Bundle

Entry point for modular AI/ML research idea discovery. Use when the user wants to find, evaluate, sharpen, or execute paper-oriented AI research ideas. Routes through literature bootstrapping, signal mining, problem formulation, claim formation, prior-work triangulation, scope gating, decision-value experiments, reviewer risk checks, and paper-shape planning while maintaining research_state artifacts.

pangzhenying2025 Skill

Skill for applying quantum computing algorithms to simulate battery electrochemistry at the molecular level, covering variational quantum eigensolver (VQE) for molecular ground states, quantum phase estimation for reaction energetics, density functional theory acceleration, and hybrid classical-quantum workflows for battery material discovery. Covers 8 topics across quantum-computing domain. Includes 8 skill files covering ASTM E3076 - Standard Guide for ICME Verification and Validation, Battery500 Consortium Performance Targets, CVRP Benchmark Instances (Augerat, Christofides sets), ECE R94 - Frontal Impact Protection, ECE R95 - Side Impact Protection, EDIFACT DELFOR/DELJIT - Delivery Forecast and JIT Messages, ETSI QKD Standards (GS QKD 004, GS QKD 014), ETSI TS 103 097 - Security Headers and Certificates for ITS and more.

houjingyi00417-hub Skill

Use when the user is doing AI/ML work in a scientific domain 鈥?biology, chemistry, physics, astronomy, climate, genomics, materials science, medicine, ecology, energy, conservation, engineering, mathematics, scientific reasoning, drug discovery, protein design, weather modeling, theorem proving, single-cell, PDE solving, or anything similar. Hugging Science (huggingscience.co) is a curated catalog of scientific datasets, models, blog posts, and interactive Spaces; the `hugging-science` org on Hugging Face hosts community datasets, models, and demo Spaces. This skill helps you discover the right resource AND actually use it 鈥?loading datasets via `datasets`, running models via `transformers` or the HF Inference API, calling Spaces like BoltzGen via `gradio_client`, and citing blog posts for methodology. Trigger this skill whenever a user mentions a scientific ML task, asks for "a dataset/model for X" where X is a scientific topic, wants to fine-tune on scientific data, asks about protein / molecule / genome /

houjingyi00417-hub Skill

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

idoforgod Bundle

사용자의 비전·목표·행동 계획 진척을 *주간·월간·분기·연간* 4단위 정기 점검으로 추적·평가·재조정하는 진척 추적 스킬. **결정론 환원** — 날짜 계산·다음 점검 일정 산출·달성률 분류(✓/△/✗)·OKR 점수 분류(0.0-0.3/0.4-0.6/0.7-1.0)·Pivot 트리거 판정·빗나감 패턴 감지·자동 추천 단위 선정·캘린더 계산(매월 마지막 금요일·첫 일요일)·완수율 산출·양식 렌더링·할루시네이션 패턴 차단은 *반드시* 동봉된 `scripts/progress_review.py` 결정론 모듈을 호출해 산출한다 (LLM 자연어 추정 금지). 4단위 점검 사이클 — ① **주간 점검(매주 일요일 30분)** — 주간 행동 완수율 + 다음 주 계획 ② **월간 점검(매월 마지막 금요일 1시간)** — 월 마일스톤·KPI 달성도 + 패턴 식별 ③ **분기 점검(분기 마지막 주 2시간)** — STG 진척률·재조정·Pivot 결정 ④ **연간 점검(12월·생일 주간 반나절)** — LTG 궤도 점검 + 비전 재선언. 각 점검 단위마다 *다른 도구·질문·산출물* — 주간은 빠른 체크리스트, 월간은 KPI 표, 분기는 회고 양식 + Stop/Start/Continue 분석, 연간은 비전 재선언 + 5년 궤도 재검토. 빗나갔을 때 *실패가 아닌 학습 신호*로 정상화 — 빠진 행동을 *데이터*로 보고 *시스템 개선* 패턴 추출. vision-strategy-coach Step 5(측정·평가)를 단독 깊이 도구로 펼친 것. 사용자가 "정기 점검", "주간/월간/분기 회고", "progress review", "비전 재조정", "KPI 점검", "Pivot 결정", "연말 회고", "신년 비전 재선언"을 언급하거나 비전·목표가 *살아있는 문서*로 갱신되도록 정기 추적 시스템을 요청할 때 발동한다. 박사님 단행본·강의·사역 사이클 점검·교회 청년부 진로 추적·신년 비전 점검자를 위해 설계되었다. vision 시리즈의 *루프 닫는 모듈* — 진단·처방의 결과를 *지속 가능한 시스템*으로 정착시킨다.

houjingyi00417-hub Skill

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

houjingyi00417-hub Skill

PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis. For pre-trained models and diverse featurizers use deepchem; for benchmark datasets use pytdc.

duaooo Bundle

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria.

idoforgod Bundle

사용자의 *영감·꿈·소망*을 측정 가능한 *현실 목표*로 변환하는 워크북 스킬. 명료해진 비전 한 문장(vision-clarity-coaching 산출물 또는 사용자 입력)을 받아 SMART 원칙 + Backcasting + OKR 3가지 검증된 프레임워크를 결합해 *5년 장기 목표 → 1년 단기 목표 → 1분기 목표 → 1주 마일스톤 → 내일 아침 첫 한 걸음*까지 단계적으로 분해한다. 5단계 변환 — ① **영감 원본 청취**(추상적 표현 그대로 받음) ② **SMART 검증**(Specific·Measurable·Achievable·Relevant·Time-bound 5축 점검) ③ **Backcasting**(미래에서 현재로 거꾸로 내림 — 5년→1년→1분기→1주→내일) ④ **OKR 변환**(Objective + 3~5 Key Results 형식으로 측정 지표화) ⑤ **첫 한 걸음**(*내일 아침 30분 안에 할 수 있는* 구체 행동까지 내림). **본 스킬의 결정론 환원 — 날짜 계산·SMART/OKR/Backcasting 구조 검증·인용 출처 매핑·OKR 채점 척도는 모두 lib/ 파이썬 모듈이 처리하며, LLM은 *각 단계의 콘텐츠*만 채운다(할루시네이션 구조적 차단).** vision-readiness Reframing·Strategy 점수가 있으면 활용 — 점수 낮으면 더 두꺼운 안내, 높으면 자율성 부여. 사용자가 "꿈을 목표로", "영감 변환", "SMART 목표", "OKR 만들기", "Backcasting", "비전을 실행 가능하게", "측정 가능한 목표", "내일 첫 한 걸음"을 언급하거나 막연한 영감·꿈을 *측정 가능한 형태*로 변환을 요청할 때 발동한다. vision-strategy-coach의 Step 2~3을 *단독 깊이 워크북*으로 펼친 것. 박사님 단행본 프로젝트·강의 청중·교회 청년부·진로 전환자를 위해 설계되었다.

l3mpire Skill

Generates a structured cold call script from a target description (job title, company type, industry, trigger, etc.). Use this skill whenever the user wants to write a cold call script, says "give me a call script", "how do I open this call", "write me a cold call for [persona]", or describes a target and needs a phone outreach framework. Always produces a full script following the 6-part framework: opener, permission-based framing, 3 pain hypotheses, discovery questions, mini proof, and meeting ask.

idoforgod Bundle

TLDR — Jerome C. Glenn (V3.0 06장 §III.B) Consequence Linker sub-skill + 박사님 2026-05-11 6차 강화. **vision-foresight-futures-wheel** 마스터 전용. Glenn 원전 single/double/triple line distinction을 **6 line thickness로 확장** (Quaternary=quadruple, Quinary=quintuple, Senary=sextuple). NSA Snyder cross-linkage + feedback loop + contradiction detection + ⭐ **6차 graph 전체 sign reversal counter (SRS)** + ⭐ **per-lineage reversal trace**. ## Triggers — INTERNAL ONLY. 마스터 Cycle 4·7에서 자동 호출. 사용자가 'single/double/triple lines', 'cross-linkage', 'feedback loop', 'contradiction', 'NSA 사례', 'SRS 측정', '6차 graph', 'sign reversal counter', '세옹지마 추적' 명시 시 발동. ## Detailed Methodology — Glenn (2009) §III.B + Figure 4 + 박사님 2026-05-11 6차 강화. 8 Phase: ① **Phase 1 6-Line Distinction** — single·double·triple·**quadruple·quintuple·sextuple** line thickness로 6차 표현. ② **Phase 2 Cross-linkage Discovery** — 다중부모·cross-domain jump·skip-level. ③ **Phase 3 Feedback Loop Detection** — positive·negative loop (Glenn highways 사례). ④ **Phase 4 Contradiction De

idoforgod Bundle

TLDR — INTERNAL Sub-skill. vision-foresight-scenarios 대표 마스터의 1번째 sub-skill. Glenn & TFG V3.0 19장 Section III Schwartz 6-step Step 1 + Bishop SRI/Shell/GBN workshop + Section III Key Points verbatim 풀 구현. **Focal Issue Definer AI Agent** — Schwartz Step 1 verbatim: *"identify the focal issue or decision"*. Bishop workshop 양식 verbatim: *"What is the most important issue concerning [domain] over the next 10 years?" "What will stay the same about this issue that will limit its alternative futures?" "What is changing about this issue that will alter its future?"*. Section III Key Points 강제 verbatim: *"The most useful scenarios are sharply focused"* + *"The best defense is to define the focus from the outset"* + *"What planning questions need to be addressed? What variables are we most likely to forecast in order to address these concerns?"*. **DEFAULT: Sharpened single-statement focal issue + Bishop 3 questions (6-8 persona aggregation) + Schwartz planning questions + Time horizon·Spatial scope·Stakeholder 정의 → 다

l3mpire Skill

Analyzes sales call transcripts to produce deep, structured persona intelligence reports. Use this skill whenever the user wants to understand their buyers better, extract insights from call recordings, build persona profiles, or analyze patterns across discovery calls — even if they just say "analyze my calls", "what are my buyers saying", "build a persona", "extract insights from transcripts", or share transcripts via CSV, MCP (Claap, Modjo, Gong, Chorus), or raw text paste. Always produces a full persona report with goals, pains, objections, feature requests, verbatims, buying signals, and strategic recommendations.

sol1986 Bundle

Audit and fully implement SEO and GEO (AI discoverability) across a Lovable project. Use this skill whenever someone wants to optimize their Lovable site for search engines or AI tools, improve Google rankings, add structured data/schema, create a sitemap or robots.txt, add Open Graph tags, build an llm.html page for AI discovery, or says things like "optimize my Lovable site", "add SEO to my project", "make my site discoverable by AI", "set up schema markup", "improve my Lighthouse score", or "help ChatGPT/Perplexity find my site". Always use this skill -- do not attempt to implement SEO from memory. Even if the request seems narrow ("just add meta tags"), use this skill to ensure nothing is missed.

mangiapanejohn-dev Skill

BluOS CLI (blu) for discovery, playback, grouping, and volume.

bahadir-digital Skill

Birkaç fikir notundan veya feature isteğinden tam Ürün Gereksinim Dokümanı (PRD) çıkaran skill. Amaç, kapsam, kullanıcı senaryoları, başarı kriterleri ve teknik gereksinimler içerir. Ürün yöneticileri, proje liderleri, yazılım takım liderleri için. Ürün fikri veya feature isteği paylaşıldığında tetiklenir.

bahadir-digital Skill

Departman veya ekip hedefinden ölçülebilir, zaman tanımlı ve sahibi belli OKR (Objectives and Key Results) seti hazırlayan skill. Strateji planlaması, çeyreklik hedefleme, performans yönetimi için. Bir hedef veya stratejik öncelik paylaşıldığında tetiklenir.

gil-kapel Bundle

Turn a rough product idea into a usable PRD with problem statement, users, scope, flows, metrics, acceptance criteria, risks, and open questions. Use when the user asks for a PRD, product spec, feature definition, discovery write-up, or planning document before UX, architecture, or coding starts.

gil-kapel Bundle

Translate a PRD into technical decisions, data shape, boundaries, folder structure, and implementation slices. Use when the user asks for architecture, system design, stack choices, app structure, APIs, repositories, services, or a tech lead handoff before coding starts.

yht0827 Bundle

Use when 기능 아이디어, 요구사항, feature spec, PRD, user story, acceptance criteria를 구현 전에 명확한 문서로 정리해야 할 때.

nicolasestrem Skill

a senior search specialist with expertise in advanced information retrieval and knowledge discovery

yht0827 Bundle

Use when PRD 기반 장기 작업을 Ralph 방식으로 쪼개고 prd.json, progress.txt, passes 상태 기반 반복 실행 흐름을 정리하거나 적용해야 할 때.

yht0827 Bundle

Use when PRD markdown, 요구사항 문서, 기능 설명을 Ralph 실행용 prd.json으로 변환하거나 기존 prd.json의 story 크기, priority, acceptance criteria, passes 상태를 검증해야 할 때.

wbx125133 Bundle

完整项目规范（PRD）生成器——把一个产品想法转化成可直接喂给 Claude Code / Cursor 的 10 模块完整规范文档。自动检测并继承 BRD.md / MRD.md 的交接区数据，避免重复提问。当用户提到"帮我写个PRD"、"我想做一个XX"、"帮我梳理需求"、"我要vibe code一个产品"、"帮我写项目规范"、"coding spec"时立即触发。也适用于"帮我把这个想法变成可执行的文档"、"我想vibe code一个产品出来"、"帮我理一下做什么"等表达。即使用户只说"我想做个XX"或"帮我想想这个怎么做"，只要最终目的是产出一份可供 AI 编程 Agent 执行的 PRD，都应触发此 skill。与 ai-agent-prd-writer 的区分：ai-agent-prd-writer 是工作场景的正式 PRD（给开发团队看），本 skill 是给 AI 编程 Agent 看的项目规范（用户直接拿去 vibe coding）。

picard1701ent Bundle

Plan and supervise end-to-end model/paper reproduction projects. Use when a user asks to reproduce a method, define an experiment roadmap, manage resources/risks, or produce a final reproducibility report.

blurlzy Skill

Retrieve official Microsoft technology information from Microsoft Learn and Microsoft Release Communications. Use this skill for ANY question about Microsoft technologies including Azure, Microsoft Fabric, Power Platform, Microsoft 365, Entra ID, Microsoft Graph, GitHub, Visual Studio, .NET, Windows, Copilot, AI Foundry, and related developer tools. Triggers include questions about features, configuration, deployment, troubleshooting, APIs, SDKs, CLI commands, pricing tiers, service limits, or best practices. ALSO use for questions about Azure service retirements, deprecations, breaking changes, what's new, release notes, roadmap, release plan, recent updates, upcoming features, M365 roadmap, or Azure updates. Always use BEFORE answering from general knowledge to ensure responses are grounded in current, authoritative documentation.

vikenpatel14 Skill

Manage JIRA issues, sprints, and boards using the Atlassian MCP server for QA testing workflows. Use when the user mentions JIRA, tickets, issues, sprints, backlog, board, standup, bugs, testing, QA, regression, defects, or wants to create, update, search, or track work items.

rycen7822 Skill

Codex curated Hugging Face skill for using Hugging Face paper pages, paper collections, related model/dataset links, and research discovery workflows.

run077 Skill

协助产品经理生成专业的产品需求文档（PRD）。Use when turning product ideas into structured PRDs, collecting requirements interactively, analyzing competitors, generating flows, or reviewing PRD content.

santosomar Bundle

Analyze MITRE ATT&CK T1424 Process Discovery in the mobile matrix. Use for TTP triage, detection engineering, hunting, defensive emulation planning, mitigations, incident response mapping, ATT&CK coverage, or questions mentioning T1424, Process Discovery, or mobile ATT&CK. Adversaries may attempt to get information about running processes on a device.

santosomar Bundle

Analyze MITRE ATT&CK T1418 Software Discovery in the mobile matrix. Use for TTP triage, detection engineering, hunting, defensive emulation planning, mitigations, incident response mapping, ATT&CK coverage, or questions mentioning T1418, Software Discovery, or mobile ATT&CK. Adversaries may attempt to get a listing of applications that are installed on a device.