OpenSkillIndex← back to search
claude-codeproductivity

Vibecosystem recall

Query the memory system for relevant learnings from past sessions using semantic search.

install
source · Clone the upstream repo
git clone https://github.com/vibeeval/vibecosystem
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/vibeeval/vibecosystem "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/recall" ~/.claude/skills/vibeeval-vibecosystem-recall && rm -rf "$T"
manifest: skills/recall/SKILL.md
tags
#semantic-search#memory-retrieval#knowledge-management#postgres#embeddings
source content

Recall - Semantic Memory Retrieval

Query the memory system for relevant learnings from past sessions.

Usage

/recall <query>

Examples

/recall hook development patterns
/recall wizard installation
/recall TypeScript errors

What It Does

  1. Runs semantic search against stored learnings (PostgreSQL + BGE embeddings)
  2. Returns top 5 results with full content
  3. Shows learning type, confidence, and session context

Execution

When this skill is invoked, run:

cd $CLAUDE_OPC_DIR && PYTHONPATH=. uv run python scripts/core/recall_learnings.py --query "<ARGS>" --k 5

Where 

<ARGS>
is the query provided by the user.

Output Format

Present results as:

## Memory Recall: "<query>"

### 1. [TYPE] (confidence: high, id: abc123)
<full content>

### 2. [TYPE] (confidence: medium, id: def456)
<full content>

Options

The user can specify options after the query:

  • --k N
    - Return N results (default: 5)
  • --vector-only
    - Use pure vector search (higher precision)
  • --text-only
    - Use text search only (faster)

Example: 

/recall hook patterns --k 10 --vector-only