bootstrap-memory

Seed OpenMemory with key prompts and decisions using simhash deduplication.

1|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/kelsi-andrewss/claude-multi-agent-pipeline --skill bootstrap-memory
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bootstrap-memory
Source: https://github.com/kelsi-andrewss/claude-multi-agent-pipeline/tree/main/skills/bootstrap-memory
Command: npx skills add https://github.com/kelsi-andrewss/claude-multi-agent-pipeline --skill bootstrap-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Consolidates project knowledge into OpenMemory from key prompts and active decisions, ensuring per-entry deduplication and safe re-runs.

Core Features & Use Cases

  • Incremental seeding of OpenMemory with key prompts found in ~/.claude/.claude/tracking/key-prompts/, applying per-entry dedup checks to avoid duplicates.
  • Shadow active decisions by indexing decision summaries into OpenMemory, linking entries to decision IDs and maintaining provenance.
  • Store metadata such as simhash, sector, and IDs to support robust semantic search, traceability, and future retrieval.

Quick Start

Run bootstrap-memory to seed OpenMemory with current key prompts and active decisions.

Frequently Asked Questions about bootstrap-memory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I consolidate project knowledge into OpenMemory without creating duplicate entries?

Seed OpenMemory with project knowledge by indexing key prompts and active decisions while applying simhash-based per-entry deduplication checks to prevent duplicates. This ensures safe re-runs and incremental knowledge curation.

What is the best way to index active decisions for future semantic retrieval?

Index active decision summaries into OpenMemory by linking entries to decision IDs and storing metadata such as simhash, sector, and IDs. This maintains provenance and supports robust semantic search and traceability for future retrieval.

How does simhash-based deduplication work when seeding a memory store?

Simhash-based deduplication computes a fingerprint for each prompt and decision entry before storage. It checks these fingerprints against existing OpenMemory records to skip duplicates, allowing safe incremental seeding without data redundancy.

Can I re-run knowledge curation scripts safely without overwriting existing memory entries?

Yes, you can safely re-run knowledge curation because the seeding process applies per-entry dedup checks. It evaluates simhash fingerprints for each prompt and decision before storage, preventing duplicate records during repeated executions.

Do I need specific file paths to start indexing prompts and decisions into OpenMemory?

Yes, the seeding process requires reading project knowledge from key prompts located in the ~/.claude/.claude/tracking/key-prompts/ directory, along with stored active decisions, to index them into OpenMemory with appropriate metadata.

Why does incremental memory seeding preserve metadata tags like sector and decision IDs?

Incremental memory seeding preserves metadata tags like sector, simhash, and decision IDs to maintain data provenance. This explicit metadata tagging enables robust semantic search capabilities and ensures traceability back to original project decisions.