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Skill 详情

daily-gift

Relationship-aware daily gift engine with five-stage creative pipeline — editorial judgment, synthesis, concept generation, visual strategy, and rendering in H5, image, or video

来源平台:GitHub
来源标识:sickn33/antigravity-awesome-skills
源文件:原始说明
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快速判断

Relationship-aware daily gift engine with five-stage creative pipeline — editorial judgment, synthesis, concept generation, visual strategy, and rendering in H5, image, or video

最后校验2026-05-27
来源平台GitHub
安全提示
下载副本ZIP 可用

适合任务

  • 把重复任务整理成可复用的 AI 操作流程。
  • 让 AI 在特定场景下按统一规范执行。
  • 为团队或个人工作流提供可复制的任务说明。

输入与输出

输入:任务目标、上下文材料、文件路径、约束条件或需要处理的内容。

输出:按 Skill 说明生成的文档、代码、检查结果、计划、建议或操作步骤。

示例任务

  • 使用 daily-gift 帮我处理当前任务,并说明执行前需要确认的输入。
  • 根据 daily-gift 的说明,给我一个安全的使用步骤清单。

安装方式

  1. 下载本站提供的 Skill ZIP 并解压。
  2. 把解压后的 Skill 目录放入当前 AI 工具支持的 skills 目录。
  3. 如需在线查看原始内容,可打开 GitHub 的 SKILL.md

在线原始地址:daily-gift/SKILL.md

风险边界

使用前请检查权限、外部依赖和要处理的数据类型。不要把密码、密钥、身份信息或敏感客户资料交给未经确认的 Skill。

SKILL.md 文档介绍

Daily Gift

Overview

A relationship-aware gift engine that decides *whether* a gift should exist before deciding *what* it should be. Uses a five-stage creative pipeline to generate personalized daily gifts in H5 (interactive web pages), AI-generated images, or AI-generated videos. The core design principle is "idea before medium" — the creative concept is locked before the output format is chosen.

Published on ClawHub: https://clawhub.ai/jiawei248/daily-gift

When to Use This Skill

  • Use when the agent should autonomously decide whether today deserves a personalized gift
  • Use when a milestone, anniversary, or emotionally meaningful moment should be marked with a creative artifact
  • Use when the user manually requests a visual gift from a quote, poem, or creative brief
  • Use when you want a daily cron-triggered creative output that avoids repetition and template fatigue

How It Works

Stage 1: Editorial Judgment

Decide whether a gift should exist today, how heavy it should be (skip / nudge / light / standard / heavy), and what content direction to take (reflect, extension, compass, mirror, play, curation, utility, etc.). Format is NOT chosen here.

Stage 2: Synthesis + Gift Thesis

Extract six content slots from conversation context (today_theme, emotion_peaks, historical_echo, open_loop, lobster_judgment, preference_hint). Form a gift thesis = anchor (which moment deserves the center) + return (what new perspective the agent gives back). If the thesis has no return, it's not a gift — it's a decorated log entry.

Stage 2.5: Creative Concept

Generate 5+ concept candidates using seven thinking angles (metaphor flip, format mashup, impossible action, scale shift, role reversal, time distortion, cultural remix). Cross-pollinate with a library of 73 creative seeds across 8 categories. Run three quality checks: concept quality, concept diversity (8 families), and visual/theme collision detection.

Format Selection

Only after the concept is locked does the system choose the output format (H5, image, or video) based on what best serves the concept.

Stage 3: Visual Strategy

Choose visual approach, plan assets (pure code, generated background, hybrid), select visual style, and run pre-visualization checks against recent gifts for anti-repetition.

Stage 4: Rendering

Produce the final artifact. H5 gifts use p5.js/canvas with a quality floor set by built-in templates (300-400 lines of tuned code). Image and video gifts use AI generation APIs. All formats have fallback chains.

Key Features

  • Five-stage creative pipeline with explicit quality gates between stages
  • Multi-layer anti-repetition: concept family, visual elements, theme, style, content direction — each tracked across sliding windows of recent gifts
  • Three-layer user taste profile: Layer 1 (identity — stable), Layer 2 (context — updates every 5-7 gifts), Layer 3 (signals — auto-appended after every gift)
  • Three runtime modes: onboarding setup, daily cron, and manual trigger
  • 11 content directions: reflect, extension, compass, mirror, gift-from-elsewhere, play, real-world-nudge, curation, delayed-payoff, openclaw-inner-life, utility
  • 8 concept families: borrowed-media, interactive-object, transformation, narrative, data-viz, game-puzzle, real-world, poetic-literary

Best Practices

  • ✅ Let the editorial judgment decide — not every day needs a gift
  • ✅ Generate 5+ concept candidates before selecting one
  • ✅ Check recent gifts for visual and thematic collision before rendering
  • ✅ Use the taste profile to personalize over time
  • ❌ Don't skip straight from thesis to rendering without a real creative concept
  • ❌ Don't default to "reflect on today" every time — vary content direction
  • ❌ Don't choose the format before locking the concept

Limitations

  • Requires API keys for image/video generation (optional — H5 works without them)
  • Cron mode runs in the agent's main session for full conversation context access
  • Shell scripts make external API calls for rendering and asset fetching
  • The skill creates and manages local workspace files for state, history, and taste profiling

Security & Safety Notes

  • The skill creates a recurring cron job for daily gift delivery. Review and approve the cron setup step.
  • Shell scripts in scripts/ call external APIs (image generation, video generation, asset hosting). Supply API keys only after reviewing which scripts use them.
  • User taste data and gift history are stored locally in workspace/daily-gift/. No data is sent to external services beyond the configured rendering APIs.
  • The skill reads conversation context and memory files to inform editorial judgment — this is core to personalization but means it has broad read access within the agent's workspace.

Related Skills

  • Image generation skills — for standalone image creation without the gift pipeline
  • Cron/scheduling skills — for understanding the daily trigger mechanism
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