Configure persistent memory search for Moltbot/Clawdbot agents to retain context across sessions.
Works with
Add memorySearch config block with provider (Voyage, OpenAI, or local), sources (memory files and/or sessions), and relevance thresholds
Create a workspace structure with MEMORY.md for curated long-term facts and memory/logs/ for daily timestamped logs
Supports three embedding providers; Voyage recommended but local option available without API keys
Includes troubleshooting for common
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmemory-setupExecute the skills CLI command in your project's root directory to begin installation:
Fetches memory-setup from sundial-org/awesome-openclaw-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-setup. Access via /memory-setup 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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Transform your agent from goldfish to elephant. This skill helps configure persistent memory for Moltbot/Clawdbot.
Add to ~/.clawdbot/clawdbot.json (or moltbot.json):
{
"memorySearch": {
"enabled": true,
"provider": "voyage",
"sources": ["memory", "sessions"],
"indexMode": "hot",
"minScore": 0.3,
"maxResults": 20
}
}
In your workspace, create:
workspace/
├── MEMORY.md # Long-term curated memory
└── memory/
├── logs/ # Daily logs (YYYY-MM-DD.md)
├── projects/ # Project-specific context
├── groups/ # Group chat context
└── system/ # Preferences, setup notes
Create MEMORY.md in workspace root:
# MEMORY.md — Long-Term Memory
## About [User Name]
- Key facts, preferences, context
## Active Projects
- Project summaries and status
## Decisions & Lessons
- Important choices made
- Lessons learned
## Preferences
- Communication style
- Tools and workflows
| Setting | Purpose | Recommended |
|---|---|---|
enabled |
Turn on memory search | true |
provider |
Embedding provider | "voyage" |
sources |
What to index | ["memory", "sessions"] |
indexMode |
When to index | "hot" (real-time) |
minScore |
Relevance threshold | 0.3 (lower = more results) |
maxResults |
Max snippets returned | 20 |
voyage — Voyage AI embeddings (recommended)openai — OpenAI embeddingslocal — Local embeddings (no API needed)memory — MEMORY.md + memory/*.md filessessions — Past conversation transcriptsboth — Full context (recommended)Create memory/logs/YYYY-MM-DD.md daily:
# YYYY-MM-DD — Daily Log
## [Time] — [Event/Task]
- What happened
- Decisions made
- Follow-ups needed
## [Time] — [Another Event]
- Details
Add to your AGENTS.md for agent behavior:
## Memory Recall
Before answering questions about prior work, decisions, dates, people, preferences, or todos:
1. Run memory_search with relevant query
2. Use memory_get to pull specific lines if needed
3. If low confidence after search, say you checked
memorySearch.enabled: true in configclawdbot gateway restartminScore to 0.2 for more resultsmaxResults to 30VOYAGE_API_KEY in environmentOPENAI_API_KEY in environmentlocal provider if no API keys availableTest memory is working:
User: "What do you remember about [past topic]?"
Agent: [Should search memory and return relevant context]
If agent has no memory, config isn't applied. Restart gateway.
{
"memorySearch": {
"enabled": true,
"provider": "voyage",
"sources": ["memory", "sessions"],
"indexMode": "hot",
"minScore": 0.3,
"maxResults": 20
},
"workspace": "/path/to/your/workspace"
}
Without memory:
With memory:
Goldfish → Elephant. 🐘
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
memory-setup has been reliable in day-to-day use. Documentation quality is above average for community skills.
memory-setup fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for memory-setup matched our evaluation — installs cleanly and behaves as described in the markdown.
memory-setup has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: memory-setup is focused, and the summary matches what you get after install.
We added memory-setup from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
memory-setup is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: memory-setup is the kind of skill you can hand to a new teammate without a long onboarding doc.
memory-setup reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: memory-setup is focused, and the summary matches what you get after install.
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