GitHub
doc-from-examples
過去資料の「型」に合わせて新規ビジネス文書を作成する。提案書・稟議・PRDを書くとき、過去資料と同じ形式で作りたいときに使う。
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Development AI Skills
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GitHub
subagent-driven-development
サブエージェント駆動開発スキル。タスクごとに新しいサブエージェントを派遣し、2段階レビュープロセスで品質を確保。
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GitHub
template-miner
過去資料からテンプレ・スタイルガイド・チェックリストを抽出して資産化する。テンプレが無い、文書品質がバラつく、過去資料を活用したいときに使う。
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GitHub
codex-cli
OpenAI Codex CLIを起動・操作するスキル。マルチエージェント連携、コード生成の委譲、サブエージェントとしてCodexを活用したいときに使う。
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GitHub
handover
保守・運用引継ぎ書を作成する。運用移行、引き継ぎ時に使う。
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GitHub
systematic-debugging
体系的デバッグスキル。根本原因調査を先に行い、修正は後に行う規律あるアプローチ。
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GitHub
stakeholder-register
ステークホルダー登録簿を作成する。関係者分析、ステークホルダー管理時に使う。
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GitHub
analysis-retrospective
Post-analysis learning and process improvement. Use when completing major analysis projects, documenting lessons learned, or improving team analytical practices.
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GitHub
peer-review-template
Structured peer review for analytical work. Use when reviewing teammates' analysis, providing constructive feedback, or establishing analysis quality standards.
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GitHub
sql-to-business-logic
Translate SQL queries into plain language business logic. Use when documenting queries, explaining analysis to non-technical stakeholders, code review, or creating user-friendly query descriptions.
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GitHub
data-catalog-entry
Create standardized metadata for data assets. Use when documenting new datasets, building data catalogs, improving data discoverability, or creating data dictionaries for teams.
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GitHub
methodology-explainer
Explain analysis methodology to diverse audiences. Use when documenting 'how we did this' sections, building trust through transparency, or teaching analytical approaches to stakeholders.
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GitHub
time-series-analysis
Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models.
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GitHub
segmentation-analysis
Customer/user segmentation with actionable insights. Use when identifying distinct customer groups, analyzing segment-specific behavior, profiling high-value segments, or testing segmentation hypotheses.
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GitHub
stakeholder-requirements-gathering
Structured requirements elicitation for analysis requests. Use when scoping new analysis projects, clarifying ambiguous business questions, or documenting analysis acceptance criteria with stakeholders.
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GitHub
root-cause-investigation
Systematic investigation of metric changes and anomalies. Use when a metric unexpectedly changes, investigating business metric drops, explaining performance variations, or drilling into aggregated metric drive...
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GitHub
executive-summary-generator
Create concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats.
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GitHub
funnel-analysis
Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, A/B testing funnel performance, or optimizing user journeys.
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GitHub
visualization-builder
Create effective, publication-ready data visualizations. Use when choosing chart types, designing dashboards, creating presentation visuals, or building interactive visualizations with best practices.
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GitHub
analysis-assumptions-log
Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
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GitHub
analysis-qa-checklist
Pre-delivery quality assurance for analysis work. Use when reviewing analysis before sharing with stakeholders, checking for completeness, validating assumptions, or ensuring clarity of recommendations.
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GitHub
insight-synthesis
Transform data findings into compelling insights. Use when converting analysis results into actionable insights, connecting findings to business impact, or preparing insights for stakeholder communication.
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GitHub
schema-mapper
Database schema understanding and relationship mapping. Use when exploring unfamiliar databases, documenting table relationships, identifying join paths, or generating ERD documentation for existing schemas.
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GitHub
metric-reconciliation
Cross-source metric validation and discrepancy investigation. Use when metrics from different sources don't match, investigating data quality issues between systems, or validating data migration accuracy.
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