Product & Planning

r-irbe Bundle

USE FOR: formalizing a Project-Euler / competition-math problem as a Lean 4 theorem that asserts a concrete numeric answer, proving it, verifying the answer actually computes (native_decide / #eval), then improving the proof from a compiler-trusted answer-check toward a kernel-checked or structural (closed-form) proof. Owns the answer-check-to-structural ladder (Bronze native_decide -> Silver decide / norm_num -> Gold characterising property / closed form) and its L3 non-triviality carve-out for legitimate native_decide answer-checks. Alias: euler-prover. DO NOT USE FOR: writing the theorem statement in isolation (use @lean-specification); one-tactic-at-a-time proof authoring or error triage (use @lean-proof); generic single-proof audit outside the carve-out (use @lean-proof-review); Mathlib API / lemma discovery (use @lean-research); project-wide quality scoring (use @lean-quality-engine); open problems with no known numeric answer (this skill requires a known target). TRIGGERS: Project Euler, competition ma

r-irbe Skill

USE FOR: Apply the review council system retroactively to an existing large Lean 4 project. Use when onboarding an existing codebase to the council review framework. Covers module discovery, dependency analysis, incremental audit scheduling, baseline establishment, gap analysis, and the catch-up RALPH cycle for bringing an existing project to full review coverage. DO NOT USE FOR: building a new council (use @lean-review-council); single proof review (use @lean-proof-review); RETRO methodology (use @lean-retro-methodology). TRIGGERS: retroactive audit, council onboarding, existing project audit, legacy Lean review.

r-irbe Skill

USE FOR: Product management for mathematical formalization projects — roadmap creation, stakeholder management, feature prioritization for formal verification artifacts, theorem portfolio management, release planning, and the business/academic value analysis of formal proofs. Complements math-project-management (scheduling/execution) with strategic product thinking. DO NOT USE FOR: project-level scheduling (use @math-project-management); strategy methodology (use @applied-strategy-analysis); engineering discipline view (use @applied-engineering-disciplines). TRIGGERS: product management, roadmap, stakeholder management, feature prioritization, formal verification PM.

r-irbe Skill

USE FOR: Project and product management for mathematical formalization projects. Covers dependency-aware scheduling, risk management for unprovable theorems, progress tracking, milestone planning, resource allocation across proof workstreams, technical debt management, and stakeholder communication. Use when planning formalization campaigns, tracking multi-module efforts, or managing the intersection of research and engineering in formal mathematics. DO NOT USE FOR: product-level PM (use @math-product-management); retro methodology (use @lean-retro-methodology); engineering discipline view (use @applied-engineering-disciplines). TRIGGERS: project management, dependency scheduling, risk management for proofs, formalization PM.

r-irbe Skill

USE FOR: epistemic discovery — picking a discovery mode (Census / Dependency / Literature / Cross-domain / Community), running an Unknown-Unknown (UU) hunting protocol at the right depth (Shallow / Standard / Deep / Exhaustive), emitting census + probe + trigger reports, anti-stagnation mechanisms, project relevance scoring. DO NOT USE FOR: a known research question (use @lean-research); council convocation on a known artifact (use @lean-review-council or @research-council); synthesis emission of known content (use @research-synthesis-engine). TRIGGERS: discovery, unknown unknown, UU hunt, epistemic discovery, census, dependency probe, cross-domain probe, community probe, anti-stagnation.

oimiragieo Skill

Full deep-dive audit loop — bugs, edge cases, backlog, current competitive web research, TDD fix waves, council-reviewed plans, re-audit until clean. Use for ultrathink mandates, /deep-dive, security audits, complete backlog, competitive analysis. Routes orchestrator by provider (Claude Opus vs Fable, Codex gpt-5.5, Cursor Auto vs Opus, agy Gemini 3.5/3.1). Spawns workflows + subagents; a peer-review council audits plans.

wulaosiji Skill

Discover and install agent skills from the open agent skills ecosystem using the Skills CLI (`npx skills`). Helps users find functionality that might exist as an installable skill for specialized domains, workflows, and tools. Use when: "找个skill", "find a skill", "有没有技能", "install skill", "搜索技能", "npx skills", "skill discovery", "扩展agent能力", "找工具", "skill marketplace". Searches skills.sh ecosystem, presents options, and can install skills globally with confirmation. Cross-references: gh-cli, skill-optimizer. Built by UniqueClub 🌐 https://uniqueclub.ai

stevennitesh Bundle

Find and rank evidence-backed improvements to an existing codebase's architecture and maintainability. Optionally create or continue a visual system map and coverage atlas. Use for baseline improvement discovery; exclude reviewing a pending diff and implementing fixes.

stevennitesh Bundle

Simplify one user-selected existing-code target without changing accepted behavior. Use only when explicitly selected; exclude new behavior, bug fixes, broad discovery, and unsettled interface or ownership decisions.

stevennitesh Bundle

Create one Markdown discovery questionnaire for one external stakeholder who owns facts, judgment, or a decision unavailable from inspectable sources and the user.

stevennitesh Skill

Use when repo work needs durable GitHub recordkeeping: issue/PRD/slice bodies, claim/status/blocker comments, PR/issue links, readiness fields, or CI/review evidence recorded in GitHub; skip ordinary local work, generic triage, PR publishing, CI debugging, and review-comment resolution when narrower workflows own them.

stevennitesh Bundle

Write or audit agent-facing skills, AGENTS.md, guides, specs, prompts, and continuation handoffs. Exclude product discovery, ordinary prose, minor wording edits, and app task transfers.

stevennitesh Skill

Use when the user asks for cleanup beyond incidental touched-file polish: explicit human-reviewability cleanup for comments/docstrings/imports/code order, cleanup discovery, continued cleanup loops, behavior-preserving refactors with structure risk, duplicated logic, module-boundary or caller-interface simplification, testability blockers, or obsolete-code removal.

synaptiai Skill

Discover available agents, skills, quality commands (lint, test, typecheck), tech stack, verification capabilities, and LSP code intelligence features via parallel environment scanning. Use when starting implementation, creating PRs, reviewing PRs, or addressing feedback. This skill MUST be consulted because assuming tools exist causes runtime failures, and assuming they do not causes missing capabilities.

synaptiai Bundle

Use when generating PRD and architecture documents that must trace back to explicit decisions. Enforces citation requirements so no spec content exists without DEC-* references.

jgsystemsconsulting Bundle

Knowledge base from the FAA AMS Lifecycle V&V Guidelines (verification and validation), Version 3.0, dated April 2017. Use for applying verification and validation across the FAA Acquisition Management System (AMS) lifecycle: the verify-vs-validate distinction (built right vs. right thing), the work-product/component/product tiers, the nine V&V planning elements, the four method catalogs (Appendix C), decision-point-gated V&V (SASP, CRD, Investment Analysis, Solution Implementation, In-Service Management), the Appendix B document checklists (PRD/APB/ISPD/PMP), and the DT/OT/IOA test triad. Scope limits: this is an FAA acquisition-V&V doctrine, NOT a general SE process model, requirements-engineering manual, or test-design textbook. It borrows its core V&V definitions from CMMI v1.2 (SEI, paraphrased) and presumes the surrounding AMS lifecycle (see the FAA SEM pack); its phase tables are policy snapshots as of April 2017 and it is thin on detailed test methods, tool specifics, and anything outside FAA acquisit

jgsystemsconsulting Bundle

Knowledge base from the NASA Systems Engineering Handbook (NASA/SP-2016-6105 Rev 2). Use for NASA's systems-engineering process model — the SE Engine and 17 common technical processes, the program/project life cycle (Pre-Phase A through F), Key Decision Points and technical reviews (MCR/SRR/PDR/CDR/…), stakeholder expectations, technical requirements, design solution, product verification and validation, and crosscutting technical management (planning, risk, configuration, interfaces, data, assessment, decision analysis). Strong for aerospace/spaceflight project SE and lifecycle gating; NASA-specific terminology (KDPs, NPR 7123.1).

jgsystemsconsulting Bundle

Knowledge base from the NASA Systems Modeling Handbook for Systems Engineering (NASA-HDBK-1009A Rev A, 2025). Use for model-based systems engineering (MBSE) wired into NASA's NPR 7123.1 SE processes: the three aspects of MBSE (language / methodology / framework), the NASA SE Engine and its two OOSEM-derived steps (Model Planning, Setting Up the Model), the Modeling Plan as a SEMP subset, the tool-agnostic NASA SE metamodel of elements and relationships across the four SysML pillars (structure / behavior / requirements / parametrics), worked SysML diagrams and tables for stakeholders, requirements, structure and V&V, generating SE work products (ConOps, MOE, MOP, TPM, V&V), the MBSE Grid framework, alternative modeling approaches (PBR, Scenario, System Specification, Verification), and the ConOps model-content template. Scope is bounded to four common technical processes (Stakeholder Expectation Definition, Technical Requirements Definition, Product Verification, Product Validation). Does NOT teach SysML itsel

killvxk Skill

使用涵盖问题、目标、市场细分、价值主张、解决方案和发布规划的 8 节综合模板创建产品需求文档（PRD）。适用于编写 PRD、记录产品需求、准备功能规格，或评审现有 PRD。

killvxk Skill

对 PRD（产品需求文档）或发布计划进行事前剖析（Pre-mortem）。将风险分类为老虎（真实问题）、纸老虎（被夸大的担忧）和大象（未被说出的隐忧），并按发布阻断、快速跟进或持续跟踪进行分级。适用于发布准备、对产品计划进行压力测试，或识别可能出错的地方。

killvxk Skill

根据工单、PRD（产品需求文档）或变更日志生成面向用户的发布说明，按类别（新功能、改进、修复）整理清晰、有吸引力的摘要。适用于编写发布说明、创建变更日志、发布产品更新公告，或总结本次发布内容。

killvxk Skill

集思广益制定团队级 OKR（目标与关键成果），对齐公司目标——定性目标与可量化关键成果。适用于制定季度 OKR、将团队目标与公司战略对齐、起草目标，或学习如何编写有效的 OKR。

killvxk Skill

将以产出为中心的路线图转化为以成果为中心的路线图，传达战略意图。将计划以反映用户和业务影响的成果陈述形式重新表达。适用于转向成果路线图、让路线图更具战略性，或将功能列表重写为成果时。

killvxk Skill

Stakeholder Map

killvxk Skill

用户访谈脚本

killvxk Skill

定义并设计产品指标看板，包含核心指标、数据来源、可视化类型和告警阈值。适用于创建指标看板、定义 KPI（关键绩效指标）、搭建产品分析体系或制定数据监控计划时使用。

killvxk Skill

基于影响力、工作量、风险和战略契合度对功能创意列表进行优先级排序，输出前 5 名推荐。适用于对功能待办列表排优先级、制定范围决策或对产品创意进行排名时使用。

killvxk Skill

将用户访谈记录整理为结构化模板，包含 JTBD（用户待办任务）、满意度信号和行动项。适用于处理访谈录音或文字记录、整理探索性访谈，或创建访谈摘要时使用。

killvxk Skill

在初始探索阶段，从产品经理、设计师和工程师视角为新产品头脑风暴功能创意。适用于启动新产品探索、探索初创产品功能，或进行初始创意构思时使用。

killvxk Skill

使用影响力 × 风险矩阵对假设进行优先级排序，并为每项假设推荐实验方案。适用于对假设列表进行分流、决定优先验证哪些假设，或应用假设优先级画布时使用。

killvxk Skill

按主题、战略契合度、影响力、工作量和风险对功能需求列表进行分析与优先级排序。适用于评审客户功能需求、对待办列表进行分流，或制定优先级排序决策时使用。

killvxk Skill

跨越 8 个风险类别（含上市策略、战略规划和团队能力）识别新产品创意中的高风险假设。适用于评估初创风险、评价新产品概念，或为新业务进行假设映射时使用。

killvxk Skill

通过产品经理、设计师和工程师多视角构思法为现有产品头脑风暴产品创意。适用于生成新功能创意、为已识别的机会点构思解决方案，或与产品铁三角协同创意时使用。

killvxk Skill

构建机会解决方案树（OST，Opportunity Solution Tree），将期望产出映射到机会、解决方案和实验，以结构化产品探索工作。基于 Teresa Torres 的《Continuous Discovery Habits》。适用于构建探索结构、将机会映射到解决方案，或决定下一步要做什么时使用。

killvxk Skill

为新产品设计精益创业实验（预型实验）。创建 XYZ 假设并推荐落地页、说明视频、预购等低成本验证方法。适用于验证新产品创意、创建预型实验或测试市场需求时使用。

killvxk Skill

从价值（Value）、可用性（Usability）、商业可行性（Viability）和技术可行性（Feasibility）四个维度识别现有产品功能创意中的高风险假设。采用多视角魔鬼代言人分析法。适用于对功能创意进行压力测试、风险评估，或准备假设映射时使用。