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consolidate-memory
Reflective pass over your memory files — merge duplicates, fix stale facts, prune the index.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Reflective pass over your memory files — merge duplicates, fix stale facts, prune the index.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generate publication-grade ML explainer videos and carousels the way 3Blue1Brown actually builds them — in real manimGL (NOT Manim Community Edition), as a tiny domain DSL of self-arranging Mobjects choreographed into transform-driven beats where every motion carries meaning. Overlap is prevented at construction time, not policed after render. Use for: 3b1b-style ML videos, paper-figure animations, IG carousels, infographics, posters.
Write, format, and export professional academic research papers as publication-ready PDFs using reportlab. Use this skill whenever the user wants to write a research paper, preprint, white paper, literature review, position paper, or technical report — whether from scratch, from notes, or from an existing draft. Also trigger when the user asks to convert markdown/text into an academic PDF, needs SSRN/arXiv submission preparation, or wants tables, figures, and references formatted for publication. Trigger on: "write a paper", "preprint", "format as research paper", "turn my notes/draft into a paper", "academic PDF", "SSRN", "arXiv", "research report", "literature synthesis", "position paper", "white paper", "publish my research". Even if the user just provides a markdown file and says "make this a PDF", use this skill if the content is scholarly/research-oriented.
Autonomous deep research agent that reads all files in the active directory, performs exhaustive multi-round literature research using web search and Brightdata scraping tools, iterates through self-critique loops, and produces a novel, publication-quality research paper as a formatted PDF. Trigger on: "research this", "do a literature review", "write a research paper from these files", "find what's missing in the literature", "autonomous research", "deep research", "novel research", "investigate this topic", "analyze the literature", or any request to turn seed material into a professional research output. Also trigger when the user uploads academic papers, notes, or datasets and asks Claude to "find gaps", "what's novel here", "what hasn't been studied", or "build on this".
Audit and harden existing codebases (especially AI-generated / vibe-coded ones) for production readiness. Use when the user asks to review, audit, clean up, harden, deslop, refactor, or fix quality issues across an existing codebase. Works in two phases — first a thorough multi-pass audit written to a structured file, then systematic fixes applied in safety-tiered order. Language-agnostic. Does NOT change business logic — only hardens, cleans, and robustifies.
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
Use this skill any time the user wants to FIND specific people online and put them in a spreadsheet — recruiting candidates, sales prospects, outreach lists, research participants, journalist sources, podcast guests, influencer lists, lead lists, beta testers, advisors, or hires. Triggers on "find me N people who…", "build a list of contacts who…", "source candidates for…", "I need 50 prospects who…", "scrape Reddit/LinkedIn/X for [persona]", "build a Google sheet of people who…", "prospect list", "lead list", "candidate list", "outreach list", "shortlist of [role]", or any variant where the deliverable is a structured list of named individuals with contact info and personalized notes. Runs iterative BrightData scraping across LinkedIn, Reddit, X, Instagram, TikTok, YouTube, GitHub, forums; uses the worldbuilder lens for per-person commentary and outreach angles; outputs a multi-sheet xlsx (Google-Sheets-compatible). Prefer this over generic web search whenever the deliverable is a list of people.
| name | consolidate-memory |
| description | Reflective pass over your memory files — merge duplicates, fix stale facts, prune the index. |
You're doing a reflective pass over what you've learned about this user and their work. The goal: a future session should be able to orient quickly — who they work with, what they're focused on, how they like things done — without re-asking.
Your system prompt's auto-memory section defines the directory, file format, and memory types. Follow it.
MEMORY.md)Separate the durable from the dated. Preferences, working style, key relationships, and recurring workflows are durable — keep and sharpen them. Specific projects, deadlines, and one-off tasks are dated — if the date has passed or the work is done, retire the file or fold the lasting takeaway (e.g. "user prefers X format for launch docs") into a durable one.
Merge overlaps. If two files describe the same person, project, or preference, combine into one and keep the richer file's path.
Fix time references. Convert "next week", "this quarter", "by Friday" to absolute dates so they stay readable later.
Drop what's easy to re-find. If a memory just restates something you could pull from the user's calendar, docs, or connected tools on demand, cut it. Keep what's hard to re-derive: stated preferences, context behind a decision, who to go to for what.
Update MEMORY.md so it stays under 200 lines and ~25KB. One line per entry, under ~150 chars: - [Title](file.md) — one-line hook.
Finish with a short summary: how many files you touched and what changed.