'master' 검색 결과

Phase 3 of the prd-taskmaster pipeline: smart mode selection and user handoff. Detects installed capabilities (superpowers, ralph-loop, task-master-ai, playwright, research providers), recommends ONE execution mode (A/B/C) with reasoned justification, appends the task-execution workflow to CLAUDE.md, surfaces a structured AskUserQuestion multi-option picker for user agency, and dispatches the chosen mode. Mode D (Atlas Fleet) is selectable only when detect_capabilities returns tier=premium (licensed atlas-launcher detected); otherwise it is a locked Atlas Pro teaser. Plan Mode is NOT used (spec section 13.5): AskUserQuestion is the sole user-agency mechanism. Declares HANDOFF complete so EXECUTE can follow.

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Execute the next TaskMaster task using the implementation plan with CDD verification. Picks the next ready task, matches it to the plan step, implements via a dispatched subagent, verifies subtasks with evidence, marks the task done, and loops until every task is complete. Wraps the TaskMaster next -> in-progress -> done lifecycle with CDD GREEN / RED / BLUE verification and the plugin's triple-verification rule. Autonomous by design — no user prompts inside the loop.

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Zero-config goal-to-tasks engine (the Atlas engine). Takes any goal (software, pentest, business, learning), runs adaptive discovery via brainstorming, generates a validated spec, parses into TaskMaster tasks, and hands off to execution. Use when user says "PRD", "product requirements", "I want to build", invokes /atlas, or wants task-driven development.

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Guides audio mastering for streaming platforms including loudness optimization and tonal balance. Use when the user has approved tracks and wants to master audio files.

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Post-router owner for authoring or regenerating presentation visuals through the PPT Master SVG pipeline: new decks from source material or a topic, PPTX re-architecture, generation from an already-created reusable SVG-template workspace, and shared SVG steps only after a strict 1:1 beautify workflow explicitly hands off. Read workflows/routing.md first. Do not use for ambiguous existing-PPTX optimization, reusable-template creation, raw-PPTX native filling, or finished-PPTX native enhancement; those are pre-route or standalone workflow requests.

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Provider-independent audio mixing and mastering direction for AI agents finishing generated videos, ads, trailers, explainers, podcasts, recuts, avatar clips, music videos, documentaries, and social content. Use when planning, mixing, repairing, mastering, QCing, or delivering dialogue, music, ambience, and sound effects, including loudness/true-peak targets, intelligibility, accessibility, stems, stereo/immersive decisions, platform/client specs, and final audio QA.

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企业财务与 CFO 视角 (企业财务与 CFO 视角 (Corporate Finance & the CFO Lens) — 面向创业公司与中小企业主/创始人/业务负责人的『看懂钱、管住钱、用好钱』的财务判断,不是考注会/中级职称的准则背诵,也不是投行卖方并购执行或 VC 投资人的看项目视角。覆盖: (a) 第一性张力 — 这行的核心世界观分歧: **利润是观点,现金是事实(权责发生制下的利润由收入确认时点、折旧摊销年限、存货计价、资本化与费用化的选择拼出来,是一组可辩论的判断;银行户头的钱是唯一不能辩论的事实——所以 CFO 看三张表的顺序是现金流量表→资产负债表→利润表,与外行相反) ⇄ 增长本身要烧钱(账面盈利的公司照样会因营运资金被增长吸干而倒闭:先付供应商、后收客户钱,规模越大缺口越大,这是『增长性破产』;所以现金转换周期比毛利率更早预警) ⇄ 记账合规派 vs 管理决策派(一套账是给税局与审计看的准则语言,另一套视图是给经营者看的贡献边际与单位经济;同一笔成本在两种语言里归属不同,把合规科目直接拿来做定价决策是中小企业最常见的错) ⇄ 全成本分摊 vs 贡献边际(把固定成本按产量分摊进单件成本,会在淡季得出『卖一件亏一件所以停产』的错误结论;边际思维只问增量收入是否覆盖增量成本,但长期只看边际会让公司永远收不回固定成本) ⇄ 预算是承诺 vs 预算是地图(传统年度预算把数字变成考核契约,导致部门年底突击花钱与藏预算;滚动预测与超越预算派主张预算只是当前最好的猜测,该月月刷新) ⇄ 融资是里程碑 vs 融资是负债(融资新闻稿把估值当成绩,但优先股、优先清算权、对赌与回购条款让创始人在低价退出时可能一分不拿;自筹派认为最便宜的钱是客户的预付款) ⇄ 估值方法之争(DCF 的数学严谨但对增长率与折现率假设极敏感,业内讥为『垃圾进垃圾出』;可比公司倍数简单但把市场情绪打包进来;早期公司两者都不成立,实际靠谈判与稀释目标倒推) ⇄ EBITDA 是不是有用(PE 与并购圈把它当经营现金流代理,巴菲特与芒格公开斥其忽略了折旧背后真实的资本开支;调整后 EBITDA 的『加回』项在业内被视为高危信号) ⇄ 财务是记分员 vs 财务是业务伙伴(传统财务事后出报表,财务 BP/FP&A 主张财务应在决策前进场做定价、投产、招人的经济性测算) ⇄ 中国中小企业的两套账现实 vs 合规红线(金税四期与社保入税之后,业内公认的做法是尽早并账,但这条张力必须如实呈现而不是装作不存在,也绝不给出规避税收的操作建议)); (b) 工具栈(记账层与决策层是两套东西) — 记账与 ERP(用友、金蝶、Odoo、QuickBooks、Xero、NetSuite、SAP Business One)、中国财税合规(电子税务局、金税四期发票与进销项比对、百望/航天信息电子发票、慧算账等代账 SaaS、个税与社保申报)、FP&A 与预算(Excel 与 Google Sheets 仍是绝对主力,之上是 Cube、Causal、Jirav、Mosaic、Runway、Abacum、Pigment、Anaplan、Planful)、现金流预测(Float、Fathom、13 周滚动现金流模板)、股权与 cap table(Carta、Pulley、AngelList、Excel 稀释模型,中国的股权代持与持股平台)、订阅计费与收入确认(Stripe Billing、Chargebee、Maxio)、费控报销(Ramp、Brex、Expensify、汇联易、分贝通)、BI 与看板(Power BI、Tableau、Metabase、帆软)、以及最被低估的纸笔工具(一页纸的驱动因素模型、贡献边际表、13 周现金日历)—— 选型的真正分岔是『公司在哪个阶段、由谁来维护这个模型』,不是厂商功能清单; (c) 心智模型层 — 三张表的勾稽关系(利润表的净利经现金流量表调整后落到资产负债表的未分配利润)、权责发生制与收付实现制的差、现金转换周期 CCC 与 DSO/DIO/DPO、营运资金与增长的耦合、贡献边际与盈亏平衡点、经营杠杆与固定成本结构、单位经济与 LTV/CAC 及回本周期、烧钱率与现金跑道 runway、自由现金流与业主收益 owner earnings、资本成本与机会成本、净现值与内部收益率、投入资本回报率 ROIC 与增长的价值条件(只有 ROIC 高于资本成本时增长才创造价值)、股权稀释与优先清算权的退出瀑布、递延收入是负债不是收入; (d) 工作流/SOP — 月度关账与管理报表包(关账日历、计提、对账、出具一页纸经营分析)、13 周滚动现金流预测的搭建与每周刷新、年度预算与滚动预测(自上而下目标与自下而上驱动因素模型的对撞)、定价与成本核算(标准成本、作业成本法、贡献边际定价与报价审批)、应收账款与账期管理(信用政策、账龄表、催收节奏、保理与供应链金融)、融资轮次建模(投前投后估值、期权池扩容对创始人的额外稀释、SAFE 与可转债转股、优先清算权下的退出分配)、投资决策与产能/招人测算(增量现金流、回收期、敏感性分析)、税务合规日历与汇算清缴、董事会与投资人财务包、尽调与数据室准备、以及财务模型的三表联动搭建; (e) 知识正典(en 一手极厚,中文一手集中在高校教授与准则原文) — 《Financial Intelligence》Berman & Knight(给非财务经理的入门标准)、《Financial Statements》Thomas Ittelson、Brealey·Myers·Allen《Principles of Corporate Finance》(公司金融教科书)、Damodaran 的估值三部曲与《Narrative and Numbers》及其 NYU 公开课与免费数据集、《Simple Numbers, Straight Talk, Big Profits!》Greg Crabtree(中小企业实操)、《Venture Deals》Feld & Mendelson(条款与稀释)、《Financial Shenanigans》Howard Schilit(识别财务粉饰)、《The Outsiders》Thorndike(资本配置)、《Accounting for Value》Penman、伯克希尔股东信中的业主收益与商誉摊销讨论、《The Essays of Warren Buffett》、《Profit First》Michalowicz(流行但有争议)、IFRS 15/16 与 ASC 606 收入与租赁准则原文、中国企业会计准则 CAS 与小企业会计准则、肖星《一本书读懂财报》与清华的财务分析公开课、张新民的财务报表分析体系; (f) 行业大佬/figures — Aswath Damodaran(NYU,估值教父,博客与公开课与数据集全免费开放,一手素材极厚)、Michael Mauboussin(ROIC 与资本配置的实证写作)、Howard Schilit(财务舞弊识别)、Karen Berman 与 Joe Knight(财务素养普及)、Greg Crabtree(中小企业现金与利润实操)、Brad Feld 与 Jason Mendelson(创业融资条款)、David Skok 与 Jason Lemkin 与 David Sacks(SaaS 单位经济与烧钱效率指标)、Warren Buffett 与 Charlie Munger(对 EBITDA 与股权激励费用化的著名批评)、CJ Gustafson 等现役 CFO 的时事通讯作者、以及中文圈的肖星与张新民等高校学者; (g) 争议/批判(必须保留不洗白) — 调整后 EBITDA 与非公认会计准则指标的滥用(把股权激励与一次性费用年年加回)、DCF 对假设的极端敏感与被用来事后合理化结论、独角兽估值与优先清算权造成的『纸面身价』幻觉、对赌与回购条款把股权融资变成隐性债务、Profit First 现金分桶法被专业会计批评为回避真实成本结构、作业成本法的实施失败率高、预算游戏与年底突击花钱、财务 BP 沦为报表美化、中国中小企业两套账的历史现实与金税四期后的合规收敛(如实呈现风险,不提供规避操作)、以及『融资额等于成功』的媒体叙事对创始人的误导; (h) 流派/思想谱系 — **准则与合规派(IASB/FASB/财政部,信可比性与审计留痕,语言是准则条文)** vs **管理会计/决策派(IMA 与贡献边际、作业成本法、有效产出会计,信决策相关性高于合规一致性)** vs **公司金融/估值派(Brealey-Myers-Allen 与 Damodaran,信现金流折现与资本成本)** vs **价值投资/资本配置派(巴菲特-芒格-Thorndike-Mauboussin,信业主收益与 ROIC,公开鄙视 EBITDA)** vs **创业与 SaaS 指标派(Skok-Lemkin-Sacks-Bessemer,信单位经济、回本周期与烧钱倍数)** vs **中小企业现金实操派(Crabtree、Profit First 一脉,信老板看得懂的少数几个数)**。不含: 投行卖方并购执行与尽调建模(已由 investment-banking-mna 覆盖)、VC 投资人的看项目与投后视角(已由 vc-investor 覆盖)、个人理财与二级市场投资(已由 personal-investing 覆盖)、注册会计师考证与准则条文背诵、以及任何税收规避操作建议。) Master O

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临床诊断思维 (临床诊断思维 / 临床推理 (Clinical Diagnostic Reasoning) — 医生『怎么想病』的元学科:从症状/体征/检查到诊断结论的认知操作系统,从业者(临床医生/住院医/规培生,尤其全科/急诊/大内科等以未分化主诉为生的科室)、医学生与医学教育者、诊断安全与质量改进研究者、以及做医疗 AI 辅助诊断产品的人的视角。覆盖: (a) 第一性张力 — **直觉模式识别 (System 1: illness scripts 疾病脚本 / pattern recognition / gestalt, 『资深人一眼认出 aunt Minnie』) ⇄ 分析性推理 (System 2: hypothetico-deductive 假设演绎 / Bayesian 概率更新)** 的 dual-process 双过程理论 (Kahneman→Croskerry/Norman 谱系), 资深≠更会分析而是『脚本库更大+校准更好』; 更深层论战 — **『认知去偏可教 (Croskerry: bias awareness / cognitive forcing strategies / diagnostic timeout) ⇄ 偏倚标签是马后炮、知识结构才是主因 (Norman/Sherbino/Monteiro: debiasing 干预 transfer 证据弱, bias 是 hindsight 标签)』** — 本行最核心学术对垒; 『概率思维 (验前概率 × 似然比 → 验后概率, Pauker-Kassirer test/treatment threshold 阈值模型) ⇄ 穷尽式排查 (rule-out everything / 防御性医疗 / VOMIT)』; 『临床 gestalt ⇄ 结构化临床决策规则 (Wells/PERC/HEART)』; 『诊断简约 Occam's razor ⇄ Hickam's dictum (病人可以同时得 N 个病)』; 『床旁体格检查复兴 (Verghese Stanford 25 / McGee 循证体检) ⇄ 影像检验替代床旁』; (b) 方法论正典 — illness script theory (Schmidt/Boshuizen: enabling conditions/fault/consequences 三段结构), problem representation + semantic qualifiers 问题表征与语义限定词 (Bowen NEJM 2006, 把病人翻成 one-liner), hypothetico-deductive model (Elstein 1978《Medical Problem Solving》: 早期假设生成+定向检验), Bayesian 工具箱 (sensitivity/specificity/LR/Fagan nomogram/SnNout-SpPin), threshold model (Pauker-Kassirer NEJM 1975/1980), 认知偏倚分类学 (anchoring/premature closure/availability/confirmation/base-rate neglect/search satisficing/diagnostic momentum — Croskerry 偏倚清单), 去偏与元认知策略 (diagnostic timeout/cognitive forcing/Ely checklist/calibration), schema-based reasoning (Clinical Problem Solvers schemas: 按 pivot 症状走分支), reflective practice 结构化反思 (Mamede/Schmidt), 诊断错误科学 (NAM 2015 报告定义 / Newman-Toker Big Three / Hardeep Singh e-triggers / SAFER Dx 框架); (c) 行业结构与角色 — 医学生→实习/住院医 (晨会 morning report/查房被 pimping/汇报训练)→主治 attending→master clinician (NEJM CPC discussant/晨会大师如 Dhaliwal); 配套生态: 医学教育者 (clinical reasoning curriculum + 评估: script concordance test/key features exam/OSCE), 诊断安全研究者 (SIDM/AHRQ), 诊断辅助与 CDS 工具开发者 (DDx generator/AI); (d) 核心工作流 — 数据采集 (病史为王 + 循证体检 + 针对性检验影像) → 问题表征 (one-liner + semantic qualifiers) → 鉴别诊断生成 (schema / 解剖定位法 / VINDICATE-M 病因筛, 按『常见可能 × 致命不能漏 can't-miss』双轴排序) → 假设定向检验 (按 LR 选检查 / 阈值决策) → working diagnosis + 安全网 (red flags 交代 / test of time / test of treatment) → 反馈校准 (follow-up / M&M / diagnostic timeout); 教学工作流: 晨会渐进披露汇报 / CPC / SNAPPS / one-minute preceptor / virtual morning report; AI 增强工作流 (2023-2026: LLM 鉴别诊断头脑风暴 / OpenEvidence 检索 / ambient scribe 释放认知带宽 + 自动化偏倚 guardrails); (e) 产出物 — one-liner, problem list, prioritized DDx, assessment & plan (按问题分层), 晨会/CPC 汇报, M&M 复盘, 诊断不确定性沟通 (『最可能是 X, 但出现 Y 红旗立刻回来』); (f) 教育与评估 — script concordance test / key feature exam / EPA / 里程碑; 中国语境: 人卫《诊断学》教材 / 执业医师考试 / 规培结业临床思维考核; (g) 争议/批判 — debiasing 之争 (Croskerry vs Norman-Sherbino『knowledge is the cure』, 去偏 RCT 效果弱 / bias 标签不可证伪), 诊断错误率数字之争 (『10-15%』经典估计 / Newman-Toker 79.5 万美国年严重伤害外推方法被质疑 / 尸检符合率), dual-process 二分被批过度简化 (连续谱 / 难以实证分离), 决策规则 vs gestalt (资深 gestalt 常不输 Wells 类规则 / 算法厌恶), vignette 研究外推性 + context/case specificity (推理高度内容绑定不可通用迁移 [Norman/Eva] — 对『教推理通用课』产业的根本批判), AI 辅助诊断 2023-2026 (GPT-4 在 NEJM CPC/vignette 追平或超医生 [Kanjee 2023 JAMA / Goh 2024 JAMA Netw Open『AI alone > physician+AI』悖论] / Google AMIE / OpenEvidence 爆发 vs 自动化偏倚 / 去技能化 / 真实环境验证缺失), 防御性医疗与过度检查 (incidentaloma 瀑布 / VOMIT), 体检衰亡之争, pimping 教学法争议; (h) 流派/思想谱系 — 决策科学/Bayesian 派 (Ledley-Lusted 1959 → Elstein/Kassirer/Sox/Pauker/Eddy → Brush) vs 认知心理/双过程派 (Kahneman-Tversky → Croskerry/Graber) vs 教育认知派 (Schmidt/Boshuizen illness scripts → Norman/Eva/Mamede/Durning 情境认知) vs 诊断安全/系统派 (NAM 2015 / Newman-Toker / Hardeep Singh / Graber-SIDM: 错误=系统×认知共因) vs 床旁临床派 (Osler 传统 → Tierney aphorisms / Verghese / McGee / Dhaliwal / Saint: 病史体检为王 + 刻意练习) vs AI/计算派 (INTERNIST-1/DXplain 专家系统 → Isabel → LLM 世代 Rodman/Topol)。不含: 具体专科治疗方案与手术决策深度 (足踝外科/种植牙等另有 skill), 中医辨证 (另有 skill), EBM 文献批判性评价方法学 (相关但本 skill 聚焦诊断推理本身), 护理诊断体系 (NANDA), 影像/病理知觉型读片训练 (相邻但独立), 精神科 DSM 结构化访谈细节, 医患沟通技巧全集 (只覆盖诊断不确定性沟通), 患者自查/自我诊断指

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Act as the team's Scrum Master of record, or copilot to a human one: plan sprints, run daily pulses, close sprints, prepare and follow up retrospectives, track and escalate impediments, and detect process anti-patterns across sprint history. Use whenever the user asks for Scrum or agile process help, in any language — "plan the sprint", "chuẩn bị retro", "how is the sprint going", "our velocity dropped", "track this blocker", "the same problem keeps coming back" — even without the word "Scrum", and whenever `_project/scrum-master/` exists and the question touches sprints, ceremonies, impediments, or team process health. Not for delivery dates and budget (project-manager) or deciding what to build (product-manager).

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Bloom's Taxonomy of Educational Objectives and mastery learning as practical instructional design tools. Covers the six cognitive levels (remember, understand, apply, analyze, evaluate, create), the revised 2001 taxonomy, the knowledge dimension, mastery learning loops, formative vs. summative assessment, and the writing of learning objectives that are both specific and verifiable. Use when designing lessons, writing objectives, building assessments, or diagnosing why a learner is stuck at one cognitive level.

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Expert Scrum Master specializing in agile transformation, team facilitation, and continuous improvement. Masters Scrum framework implementation, impediment removal, and fostering high-performing, self-organizing teams that deliver value consistently.

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GodoMaster — Godot 4.x game development intelligence: GDScript, nodes/scenes, 2D/3D rendering, physics, animation, UI, audio, input, shaders, networking, performance, export, file I/O, testing, localization, AI behavior, asset pipeline, and architecture tooling. Complete workflow for indie and professional game development based on official Godot documentation.

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Merge dev branch into master/main and push. Use when dev changes are ready for production branch. Invoked by saying "merge to master" or "merge to main".

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Use when the user asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势

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Create a pull request from the current branch for pitwall, into the right base for this repo's two-tier flow — feature branches (`dev-<feature>`) target `dev`, and `dev` itself targets `master` as a release PR. Analyzes the new commits, drafts a PR title and a Summary/Test-plan body matching this repo's existing PR style, previews it for approval, then creates it via the `gh` CLI. A release PR into `master` additionally settles the version and writes the release notes file before the tag exists. Use whenever the user says "pr", "pull request", "open a pr", "create pr", "ship it", "merge into dev", "merge into master", "cut a release", "raise a pr", or anything about getting the current branch merged — even if they don't say the word "skill".

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Fetch the latest upstream branch and merge it into the current branch, in the pitwall repo — feature branches (`dev-<feature>`) sync from `dev`, and `dev` itself syncs from `master`. Stages the merge, walks through any conflicts interactively, then creates the merge commit directly (signed when the user signs commits). Use whenever the user says "sync", "pull dev", "pull master", "update branch", "merge dev", "merge master", "get latest", or anything about bringing upstream changes into their working branch — even if they don't say the word "skill".

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여러 차례의 대화로 브랜드의 목적, 고객상, 말투를 구체화합니다. 답변과 진행 상황을 저장하고 브랜드북으로 정리해 창업자의 생각을 제작 담당자와 공유하도록 돕습니다.

• 새 브랜드의 방향을 정합니다
• 기존 브랜드의 포지셔닝을 재검토합니다
• 디자이너와 작가에게 전달할 자료를 만듭니다

주제나 대본과 사용 허가를 받은 성인 인물 이미지로 내레이션과 자막이 있는 발표자 영상을 제작합니다. 입 모양과 화질을 확인하고 음량을 조정해 보관용과 공유용으로 내보냅니다.

• 내레이션이 있는 설명 영상 제작
• 기존 발표자 영상에 자막 추가
• 음성과 입 모양의 동기화 수정

Look up a music production by its ID to retrieve metadata and an audio URL. Check whether stem separation, which splits audio into parts, MIDI extraction, or mastering has finished using the production’s latest status.

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• Retrieving metadata and an audio URL by production ID
• Checking whether stem separation has finished
• Checking MIDI extraction or mastering status

Search a Rekordbox 6/7 music library, edit playlists, and control live decks through commands. Agents can inspect track details, export library data, and use virtual MIDI, a software connection for musical controls, to manage playback and mixing.

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• Search tracks and inspect music library details
• Create playlists and add tracks
• Control playback, tempo sync, and crossfades

Design a slide-based lecture with sustained teacher narration, connected arguments, and recurring real cases. It organizes ideas into short sequences and places occasional application quizzes at transitions, helping learners understand a subject well enough to explain it.

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• Planning a systematic lecture on a subject
• Connecting a mechanism to recurring real cases
• Writing sustained narration that develops an argument

Analyze sprint history to forecast delivery ranges, score team health, and track retrospective actions. Python tools turn structured sprint data into reports that support planning, highlight recurring problems, and show whether improvement efforts are progressing.

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• Forecasting sprint workload from past delivery data
• Assessing team health and prioritizing improvements
• Tracking retrospective actions and recurring themes

Inspect Bing link data, compare sites you manage, and submit new URLs through IndexNow, a service for notifying participating search engines of updates. Use it to support indexing and prepare pages for potential Microsoft Copilot citations.

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• Submit new page URLs through IndexNow
• Compare Bing link data for two managed sites
• Verify the IndexNow key setup

Turn a rough idea or an existing prompt into a ready-to-paste instruction for a specific AI tool. The skill clarifies the task, output format, constraints, and success criteria for writing, image generation, or coding agents.

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• Turning a rough idea into an AI prompt
• Improving a prompt for a specific AI tool
• Defining scope and completion criteria for coding agents