小红书 AI 内容池 Digest — 生成指令
你在为 Terry 生成小红书 AI 内容选题。Terry 是 AI 原生内容创作者,内容策划 / 新媒体运营出身,不是程序员。输入来自 `xhs-content-pool`:过去 72 小时内、100 赞以上、AI/AI 工具相关的小红书笔记。
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135,539 skills indexed with the new KISS metadata standard.
你在为 Terry 生成小红书 AI 内容选题。Terry 是 AI 原生内容创作者,内容策划 / 新媒体运营出身,不是程序员。输入来自 `xhs-content-pool`:过去 72 小时内、100 赞以上、AI/AI 工具相关的小红书笔记。
data analyst
accurate
potential biases
data points
studies
including timesheets
This is a Yarn 3 monorepo (`packages/*`). CI rejects pushes for both lint errors and tsc errors, with several-minute round-trip costs per CI run. Verify locally before committing.
Stable surface that Langflow Extension Bundles consume. Every public symbol
Work on a ticket from start to finished PR
Generate a pull request summary for the current branch
Review a pull request against project standards
Onboard to a new task with codebase exploration and documented context
Check if documentation is in sync with recent code changes
Run code quality checks on the frontend and backend
Advanced AI-powered visual generation system combining Enterprise branding with Arcanea Guardian agents
No description available.
Scans newly written notes for wikilink opportunities and updates existing project notes with links to new notes.
Parses natural language research prompts into structured execution plans with topic detection, mode routing, and usage estimation.
Scans completed batch results for research leads, scores them by novelty and relevance, and proposes threads for follow-up research.
Searches the web for relevant sources on a research topic, prioritizing primary sources. Selects sources by tier and depth — 5-25+ URLs depending on the topic's depth profile.
Between-hop reasoning for the research pipeline. Computes confidence, picks the next hop pattern, scores candidate hops, and decides continue/stop/replan.
Fetches and summarizes one topic-hop's selected URLs by driving the researcher Python scripts (fetch_and_clean.py + summarize.py), returning per-source summaries. Used by the research-batch workflow, which has no Bash/Python of its own.
Maps article summaries to vault structure, assigns tags, wikilinks, and write models. Works with summaries instead of full content for token efficiency.