A semantic memory toolchain that uses Pinecone to provide persistent, searchable knowledge for AI agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pinecone-memory
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install pinecone-memory using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Pinecone Memory Skill?
The Pinecone Memory Skill is a specialized integration designed to bridge local developer knowledge with high-performance vector databases. By leveraging Pinecone as a backend, it enables AI agents within the Openclaw Skills ecosystem to perform semantic searches, maintain long-term memory across sessions, and synchronize local Markdown documentation into vectorized indexes. This ensures that your coding agents have access to the right context at the right time.
Built for reliability and efficiency, this skill supports Integrated Embedding indexes, meaning it manages the heavy lifting of text chunking and vectorization natively. Whether you are building a personal knowledge base or a complex multi-agent system, the Pinecone Memory Skill provides the necessary infrastructure for scalable, intelligent data retrieval.
Pinecone Memory Skill Use Cases
- Synchronizing local markdown notes and documentation to a remote Pinecone vector index.
- Querying historical conversation logs or user preferences using semantic similarity.
- Performing automated health checks and heartbeat probes on vector database connectivity.
- Managing environment-specific data through namespace isolation for testing and production.
How Pinecone Memory Skill Works
- Environment Validation: The skill first checks for the PINECONE_API_KEY and validates index availability.
- Incremental Synchronization: It scans local directories for Markdown files, hashes their content, and syncs only modified segments to the index.
- Semantic Retrieval: When a query is issued, the skill uses Pinecone Integrated Embedding to find the most relevant context chunks.
- Status Monitoring: Continuous heartbeat and stats commands monitor index density and data visibility.
- Lifecycle Management: Integrated tools allow for full cleanup, local JSONL backups, and restoration of vector data.
Pinecone Memory Skill Setup
To get started with this Openclaw Skills component, ensure you have a Pinecone account and the necessary environment variables configured.
# Set your environment variable
export PINECONE_API_KEY='your-api-key'
# Perform an environment and index check
node ./tools/pinecone-memory.mjs check --index openclaw-memory
# Sync your local memory files
node ./tools/pinecone-memory.mjs sync --index openclaw-memory --namespace default --path MEMORY.md
Pinecone Memory Skill Data Schema & Taxonomy
The skill organizes data using a structured metadata model optimized for filtering and traceability within Openclaw Skills.
| Attribute | Description |
|---|---|
chunk_text |
The primary text content used for semantic indexing. |
source |
The origin file path or URL of the data. |
record_type |
Categorization such as core_content, qa_knowledge, or conversation_history. |
_id |
Structured identifier following the format source#chunk-n#hash. |
metadata |
Includes timestamps, author, department, and versioning information. |
Pinecone Memory Skill Advanced Features
- Incremental Sync Engine: Uses local state tracking (.pinecone-memory-state.json) to minimize API calls and sync only changed files.
- Integrated Embedding Support: Automatically handles text-to-vector conversion without requiring external embedding services.
- Write Verification: Includes a heartbeat mechanism that writes a probe and verifies visibility to ensure data integrity.
- Flexible Backup/Restore: Allows users to export entire namespaces to JSONL for local archival or migration between indexes.
SKILL.md
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