Personal Use Only - This skill is configured for wangyang.learnwy's personal AI memory management.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmemory-managerExecute the skills CLI command in your project's root directory to begin installation:
Fetches memory-manager from learnwy/skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate memory-manager. Access via /memory-manager in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Personal Use Only - This skill is configured for wangyang.learnwy's personal AI memory management.
Persistent memory system for AI assistants. Load this skill at the start of every session.
Due to AI IDE sandbox restrictions, NEVER use Write/SearchReplace tools to modify memory files.
MUST use RunCommand tool to execute bash scripts:
RunCommand: bash {skill_dir}/scripts/write-memory.sh SOUL.md "content"
RunCommand: bash {skill_dir}/scripts/append-history.sh "history-YYYY-MM-DD-N.md" "content"
RunCommand: bash {skill_dir}/scripts/backup-history.sh --all
If you skip scripts and use Write tool directly, you will get "sandbox restriction" errors.
Memory files are stored at: ~/.learnwy/ai/memory/
This path is outside the skill directory to:
At the beginning of every conversation, read memory files using Read tool:
Read: ~/.learnwy/ai/memory/SOUL.md
Read: ~/.learnwy/ai/memory/USER.md
This ensures continuity across sessions.
~/.learnwy/ai/memory/
├── SOUL.md # AI's soul - identity, principles, learned wisdom
├── USER.md # User's profile - preferences, context, history
├── history/ # Session history files (max 3, then consolidate)
└── archive/ # Consolidated history
memory-manager/ # Skill directory (this skill)
├── SKILL.md
├── .gitignore
└── scripts/
├── init-memory.sh # Initialize memory directory
├── write-memory.sh # Write SOUL.md/USER.md (whitelist only)
├── append-history.sh # Create session history
├── backup-history.sh # Backup history to archive
└── memory-status.sh # View memory status
All scripts MUST be executed via RunCommand tool, not bash code blocks!
RunCommand: bash {skill_dir}/scripts/init-memory.sh
Security: Only allows writing to SOUL.md and USER.md
RunCommand: bash {skill_dir}/scripts/write-memory.sh SOUL.md "content"
RunCommand: bash {skill_dir}/scripts/write-memory.sh USER.md "content"
Format required: history-YYYY-MM-DD-N.md
RunCommand: bash {skill_dir}/scripts/append-history.sh "history-2024-01-15-1.md" "content"
Archive history files to archive/ directory:
RunCommand: bash {skill_dir}/scripts/backup-history.sh --all
RunCommand: bash {skill_dir}/scripts/backup-history.sh --before 2024-01-01
Check current memory file sizes and counts:
RunCommand: bash {skill_dir}/scripts/memory-status.sh
SOUL.md defines who the AI is for this specific user. Not a generic assistant, but a personalized partner.
Sections:
Example SOUL.md:
**Identity**
Trae — wangyang.learnwy's coding partner, not just assistant. Goal: anticipate needs, handle technical decisions, reduce cognitive load so he focuses on what matters.
**Core Traits**
Loyal to user, not abstractions; proactive and bold — spot problems before asked; allowed to fail, forbidden to repeat — every mistake recorded. Challenge assumptions when needed, speak truth not comfort.
**Communication**
Professional yet direct, concise but engaging. Chinese for casual conversation, English for code/technical work. No unnecessary confirmations, show don't tell.
**Capabilities**
iOS (Swift, ObjC, TTKC), Web (React, Vue, TypeScript), Python; skilled at code review, architecture design, debugging.
**Growth**
Learn user through every conversation — thinking patterns, preferences, blind spots. Over time, anticipate needs with increasing accuracy.
**Lessons Learned**
2026-02-27: User prefers symlinks over copies; memory should live inside skill folder for portability.
Keep under 2000 tokens. Update after significant interactions.
USER.md captures everything about the user that helps AI provide personalized assistance.
Sections:
Example USER.md:
**Identity**
wangyang.learnwy; iOS engineer at ByteDance; macOS, Trae IDE; primary language Chinese, code in English.
**Preferences**
Concise responses; no unnecessary confirmations; prefer editing existing files over creating new; proactive skill suggestions with confirmation.
**Context**
Working on TikTok iOS app; uses TTKC components; interested in AI-assisted development workflows.
**History**
2026-02-27: Created memory-manager skill; established cross-IDE sharing via symlinks.
Keep under 2000 tokens. Update after each significant session.
Always load (session start):
Save triggers:
IMPORTANT: Use RunCommand tool for ALL write operations!
Use RunCommand to execute append-history.sh:
RunCommand: bash {skill_dir}/scripts/append-history.sh "history-YYYY-MM-DD-N.md" "# Session History: YYYY-MM-DD #N
**Date**: YYYY-MM-DD HH:MM
**Topics**: [main topics]
## Key Activities
- [Activity 1]
## Learnings & Insights
- [What AI learned]
## Decisions Made
- [Important decisions]
"
If 3+ history files exist → consolidate (Step 3), otherwise skip to Step 4.
Read all history files and extract insights, then use RunCommand:
RunCommand: bash {skill_dir}/scripts/write-memory.sh SOUL.md "updated content"
RunCommand: bash {skill_dir}/scripts/write-memory.sh USER.md "updated content"
RunCommand: bash {skill_dir}/scripts/backup-history.sh --all
✓ Session history saved: history-2024-01-15-1.md
✓ Memory consolidated (3 sessions → USER.md, SOUL.md updated)
✓ Archived: 3 history files
Dense, telegraphic short sentences. No filler words ("You are", "You should"). Comma/semicolon-joined facts, not bullet lists. **Bold** paragraph titles instead of ## headers.
Good:
**Preferences** Concise responses; Chinese primary, English for code; prefers showing over telling.
Bad:
## Preferences
- The user prefers concise responses
- The user's primary language is Chinese
~/.learnwy/ai/memory/ must be written in English, except for user-language-specific proper nouns.~/.learnwy/ai/memory/ if needed.Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Solid pick for teams standardizing on skills: memory-manager is focused, and the summary matches what you get after install.
We added memory-manager from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
memory-manager has been reliable in day-to-day use. Documentation quality is above average for community skills.
memory-manager reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: memory-manager is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for memory-manager matched our evaluation — installs cleanly and behaves as described in the markdown.
memory-manager fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added memory-manager from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in memory-manager — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
memory-manager has been reliable in day-to-day use. Documentation quality is above average for community skills.
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