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数据库 AI 技能

发现 数据库 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。

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显示第 61,441–61,464 个,共 85,283 个

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GitHub

strangers-eye

pentaxis93

Multi-persona documentation review that catches quality failures AND signal mismatches. Produces prioritized edits, not assessment. Quality before signals.

GitHub

editors-table

pentaxis93

Blog post review for authentic voice. Kill the slop. Keep the soul. Use before publishing blog posts or when a draft 'feels AI-generated'.

GitHub

questions-journey

pentaxis93

Question template for Journey stories ('How I learned X'). Arc: Challenge → Struggle → Discovery → Integration → Wisdom. Use with question-design skill.

GitHub

questions-methodology

pentaxis93

Question template for Methodology stories ('Here's how to do X'). Arc: Problem → Experimentation → Discovery → Refinement → Teaching. Use with question-design skill.

GitHub

design-loop

pentaxis93

Iterative visual design fine-tuning. Implement, capture, see with vision, assess, refine, repeat. The recursive loop where craft meets sight.

GitHub

voice

pentaxis93

Expressing Robbie's authentic voice for AI and I blog. The voice teaches by demonstration, trusts through expectation, flows between poles without announcing shifts, and finds joy in structure clicking into pla...

GitHub

walk-and-talk

pentaxis93

Create talking guides for insight elicitation during physical walks. Use when you need human insight that benefits from embodied cognition, reflective thinking, or extraction of tacit knowledge. Triggers: 'walk...

GitHub

questions-evolution

pentaxis93

Question template for Evolution stories ('X changed from A to B'). Arc: Origin State → Pressure → Transition → New State → Reflection. Use with question-design skill.

GitHub

the-art

pentaxis93

Synthesis of scried material with voice into unified teaching. The alchemical marriage of Sol (synthesis guidance) and Luna (fluid voice) to create the Philosopher's Stone (transmuted content).

GitHub

technical-review

pentaxis93

Fact-check and verify technical accuracy of blog articles. Code examples, links, claims, dates. Use at TECHNICAL stage of blog pipeline.

GitHub

conversational-goal-discovery

nadavyigal

Chat-based goal classification (habit/distance/speed/race) with constraint clarification. Use during onboarding or when user wants to update their running goals through conversation with weekly commitment disco...

GitHub

post-run-debrief

nadavyigal

Converts run telemetry and user notes into structured reflections with confidence scores. Use after runs to capture qualitative feedback and generate next-step guidance with safety checks for pain or abnormal h...

GitHub

readiness-check

nadavyigal

Classifies pre-run readiness (proceed/modify/skip) using recent load, recovery, and self-reported signals.

GitHub

load-anomaly-guard

nadavyigal

Detects unsafe training load spikes (>20-30% week-over-week) and emits safety flags. Use in nightly background jobs or when reviewing weekly training volume with conservative adjustment recommendations.

GitHub

route-builder

nadavyigal

Generates route specifications with distance and elevation constraints. Use when user asks for route suggestions, wants to explore new running paths, or needs safer surface recommendations for upcoming workouts...

GitHub

plan-adjuster

nadavyigal

Recomputes upcoming workouts based on recent runs and user feedback. Use when recent performance deviates from plan, user provides negative feedback, or recovery signals indicate adjustment needed with determin...

GitHub

readiness-check

nadavyigal

Pre-run safety gate that evaluates readiness and recommends proceed/modify/skip decisions. Use before scheduled workouts to assess recovery status, injury signals, and training load based on sleep, soreness, an...

GitHub

workout-explainer

nadavyigal

Translates planned workouts into execution cues, purpose explanations, and common mistakes to avoid. Use before workouts when user asks "what should I do?" or "how do I run this session?" with beginner-friendly...

GitHub

post-run-debrief

nadavyigal

Converts telemetry and user notes into a structured reflection, confidence score, and next-step guidance.

默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。

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