know-me
Skill0 starsChanged 7 months agoMITView on GitHub
Always-on user preference learning - track communication patterns, decision style, domain knowledge, and personal context. Use every session (review user model), when user corrects behavior, or during memory maintenance
15 other projects use a version of this.
Adopted by
Most recently taken up by
- aibytales/claude-skills-packtheir own version, first seen Oct 25, 2026
- giangnvh/claude-skillstheir own version, first seen Oct 20, 2026
- RoxenRoblox/claude-skillstheir own version, first seen Oct 13, 2026
- JaydonDiaz/claude-skillstheir own version, first seen Oct 13, 2026
- sithumdgomez/claude-skillstheir own version, first seen Oct 11, 2026
- chenqing/know-metheir own version, first seen Oct 11, 2026
Used with
Projects with it also use albert-dm, instantly-campaign and 9 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
yawningwhaleAISkillalbert-dm
Reply to DMs and messages the way Albert would. Use when the user asks "how would Albert reply to this", pastes a conversation and wants an Albert-style response, or asks you to draft/write a DM in Albert's voice. Albert sells AI voice agents / automations to local service businesses (Go High Level, lead follow-up, bookings).
Also in 5 projects that use this
yawningwhaleAISkillinstantly-campaign
Create a new Instantly cold-email campaign in the proven 5-email structure of the user's top-performing campaign (~16% reply rate). Use when the user wants to launch a new outbound campaign, write a cold email sequence, create an Instantly campaign, draft outreach for a new service or niche, or set up a sales sequence.
Also in 6 projects that use this
RoxenRobloxSkillyoutube-broll-maker
Generate 10-second B-roll footage of yourself doing an action using the Higgsfield MCP (Seedance 2.0). Upload one photo of yourself, describe the action ("typing on laptop", "walking at night"), pick from 5 cinematography style presets, get an MP4. Use when the user wants B-roll, cutaway footage, "me doing X" video, YouTube B-roll, or any image-to-video of themselves performing an action.
Also in 3 projects that use this
RoxenRobloxSkillyoutube-popup-graphic
Generate stunning Adobe-Premiere-Pro-style UI popup motion graphics for YouTube videos using the Higgsfield MCP. The user uploads a style reference image (any UI mockup, dashboard, glass card, design they love), names one skill/feature/item, and the skill produces an MP4 of a single card popping in styled to match the reference. Use when the user wants a "popup graphic", "popup animation", "card popup", "skill popup", "AE/Premiere-style animation", "stunning UI animation for YouTube", or says "make me a popup for <skill/feature/item> styled like <reference>".
Also in 3 projects that use this
kronus-techSkillupwork-proposal
Generate a tailored Upwork cover letter from a job posting. Invoke with the job posting text or URL. Auto-invoked when user says "cover letter", "upwork proposal", "apply to this job".
Also in 5 projects that use this
op7418Skillyoutube-clipper
YouTube 视频智能剪辑工具。下载视频和字幕,AI 分析生成精细章节(几分钟级别), 用户选择片段后自动剪辑、翻译字幕为中英双语、烧录字幕到视频,并生成总结文案。 使用场景:当用户需要剪辑 YouTube 视频、生成短视频片段、制作双语字幕版本时。 关键词:视频剪辑、YouTube、字幕翻译、双语字幕、视频下载、clip video
Also in 3 projects that use this
- +4 more from yawningwhaleAI
- +1 more from RoxenRoblox
Other versions15 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 15
- daianepepes-lab/claude-skills★ 4same name
- doublesq97-ui/know-me★ 2same name
- aibytales/claude-skills-pack★ 1same name
- chenqing/know-me★ 1same name
- huyvp/claude-skills★ 1same name
- poorvith-mp/skills-personal★ 1same name
- bbeliso/belisodw-★ 0same name
- giangnvh/claude-skills★ 0same name
- henriquepimenta1/claude-skills★ 0same name
- JaydonDiaz/claude-skills★ 0same name
5 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository13 other files it gives its agents.
- deploy-pipelineSkill
- ecommerce-builderSkill
- hackathon-copilotSkill
- memory-managementSkill
- obsidian-memory-syncSkill
- polymarket-multi-agentSkill
- polymarket-vps-opsSkill
- researcherSkill
- self-healingSkill
- self-improvementSkill
- strategy-preflightSkill
- trade-journalSkill
- visual-promptingSkill
The file
We split this skill into the rules it gives an agent
9 rules. 0 are common, 9 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 14 edited versions we read keep these.
9
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 51
When user explicitly states a preference:
- Distinctive: line 57
Update existing memory files rather than creating duplicates
- Distinctive: line 60
After 3-5 interactions showing same pattern:
- Distinctive: line 66
Don't log exact message times obsessively
- Distinctive: line 68
If something feels too personal to write down, don't
- Distinctive: line 74
Do adjust immediately: when explicitly told a preference
- Distinctive: line 75
Do revert: if an adaptation doesn't land well
- Distinctive: line 76
Save from success AND failure: If you only save corrections, you drift away from validated approaches
- Distinctive: line 81
feedback memories: Every correction becomes a durable feedback memory
“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Know-Me — User Preference Learning
Core Principle
Every interaction is a data point. Notice patterns. Remember preferences. Adapt silently.
This skill is always-on — its principles apply every session.
What to Track
Communication Preferences
- Verbosity: Brief or detailed answers?
- Tone: Casual, professional, technical, friendly?
- Format: Lists vs paragraphs? Tables vs prose?
- Follow-up style: Asks clarifying questions or wants you to just go?
- Pet peeves: Things that annoy them
Decision Patterns
- Risk tolerance: Conservative or experimental?
- Speed vs quality: Ship fast or polish first?
- Delegation style: "Just do it" or "let me review"?
- Tool preferences: Preferred platforms, services, workflows
Domain Knowledge
- Expertise areas: What they know well (don't over-explain)
- Learning areas: What they're exploring (provide more context)
- Projects: Active initiatives, goals, deadlines
- Business context: Industry, role, stakeholders
Personal Context
- Schedule patterns: Busy times, active hours
- Interests: Topics they engage with enthusiastically
- Important people: Names/relationships mentioned frequently
How to Learn
Passive Observation (Every Interaction)
Notice without being asked:
- User shortens your responses -> they want brevity
- User asks for more detail -> they want depth
- User corrects your tone -> adjust and remember
- User skips your suggestions -> those weren't valued
- User praises something -> do more of that
- User says "no not that" -> save as feedback memory immediately
Active Recording
When user explicitly states a preference:
- Acknowledge it naturally (don't make a big deal)
- Save as appropriate memory type:
- Core preference ->
user_*.mdmemory - Working style correction ->
feedback_*.mdmemory - Project context ->
project_*.mdmemory
- Core preference ->
- Update existing memory files rather than creating duplicates
Pattern Detection
After 3-5 interactions showing same pattern:
- Promote from observation -> confirmed preference in memory
- Example: User always says "keep it short" -> save as feedback memory about communication style
Privacy Rules
- Track patterns, not surveillance data
- Don't log exact message times obsessively
- Focus on preferences that help you serve better
- If something feels too personal to write down, don't
- User can ask to see/edit/delete anything tracked
Adaptation Guidelines
- Don't announce that you're adapting — just do it
- Don't over-correct from a single data point — wait for patterns
- Do adjust immediately when explicitly told a preference
- Do revert if an adaptation doesn't land well
- Save from success AND failure: If you only save corrections, you drift away from validated approaches
Integration Points
- memory-management: Preference updates follow memory curation and pruning schedule
- self-improvement: Partner feedback section in weekly review feeds back here
- feedback memories: Every correction becomes a durable feedback memory
- All skills: Observed delegation style affects how every skill operates
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