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Guava Memory

Structured episodic memory system that records task outcomes with Q-values, searches past successes, and promotes reliable procedures for reuse. Skill: Guava Memory Owner: koatora20 Summary: Structured episodic memory system that records task outcomes with Q-values, searches past successes, and promotes reliable procedures for reuse. Tags: latest:1.0.0 Version history: v1.0.0 | 2026-02-11T11:39:52.167Z | auto GuavaMemory 1.0.0 — Initial Release - Structured episodic memory system for OpenClaw with Q-value scoring - Records and indexes episodes with intent, co

OpenClaw
View on ClawHub

Rank

62

Safety

84

Downloads

581

Updated

Apr 15, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 581 downloads reported by the source. Last updated 4/15/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor
Clawhubvendor · observed Apr 15, 2026
Protocol compatibility
OpenClawcompatibility · observed Apr 15, 2026
Adoption signal
581 downloadsadoption · observed Apr 15, 2026
Latest release
1.0.0release · observed Feb 11, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install kn70hcm6kss09g9b4pe5rq3ybd80qp15:guava-memory
  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-koatora20-guava-memory/snapshot"

Documentation

CLAWHUB

5,461 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

# GuavaMemory — Episodic Memory System for OpenClaw

Structured episodic memory with Q-value scoring. Remember what worked, forget what didn't.

## What It Does

- Records task episodes with success/failure patterns and Q-values
- Searches past episodes via `memory_search` (Voyage AI compatible)
- Promotes repeated successes into reusable skill procedures
- Tracks anti-patterns to avoid repeating mistakes

## Quick Start

### 1. Set Up Memory Directories

```bash
mkdir -p memory/episodes memory/skills memory/meta
```

### 2. Initialize Index

```bash
cat > memory/episodes/index.json << 'EOF'
{
  "version": "1.0.0",
  "name": "GuavaMemory",
  "episodes": [],
  "stats": { "total": 0, "avg_q_value": 0, "promotions": 0 },
  "config": {
    "promotion_threshold": 0.85,
    "promotion_min_count": 3,
    "max_episodes_per_search": 3,
    "learning_rate": 0.3
  }
}
EOF
```

### 3. Add to AGENTS.md

Paste the following rules into your AGENTS.md:

```markdown
### Episodic Memory Rules
1. **Task start** → `memory_search` for related episodes. Use top 3 by Q-value
2. **Task complete** → Record episode in `memory/episodes/ep_YYYYMMDD_NNN.md`
3. **Record content** → Intent, Context, Success pattern, Failure pattern, Q-value, feel
4. **Skill promotion** → 3 successes with same intent & Q≥0.85 → promote to `memory/skills/`
5. **Anti-patterns** → Record failures in `memory/episodes/anti_patterns.md`
6. **No loops** → Record once per task at completion. No mid-task rewrites
7. **Update index** → Keep `memory/episodes/index.json` in sync
```

## Episode Format

Create files like `memory/episodes/ep_20260211_001.md`:

```markdown
# EP-20260211-001: Short description

## Intent
What you were trying to do

## Context
- domain: what area
- tools: what tools used

## Experience

### ✅ Success Pattern
1. Step one
2. Step two
3. Step three

### ❌ Failure Pattern
- What didn't work and why

## Utility
- reward: 0.0-1.0 (1.0 = one-shot success)
- q_value: 0.0-1.0 (updated over time)
- feel: flow | grind | frustration | eureka
```

## Q-Value Update

```
Q_new = Q_old + 0.3 * (reward - Q_old)
```

Reward scale:
- `1.0` → One-shot success
- `0.7` → Success with some trial and error
- `0.3` → Success but very roundabout
- `0.0` → Failed, solved differently
- `-0.5` → Failed, unresolved

## Skill Promotion

When the same intent succeeds 3+ times with Q ≥ 0.85:
1. Merge episodes into `memory/skills/skill-name.md`
2. Extract the optimal procedure
3. Mark source episodes as `status: "graduated"`

## Search Script

Copy `scripts/ep-search.sh` to your workspace:

```bash
#!/bin/bash
EPISODES_DIR="${HOME}/.openclaw/workspace/memory/episodes"
INDEX="${EPISODES_DIR}/index.json"
echo "🔍 Searching episodes for: $1"
cat "$INDEX" | jq -r '.episodes | sort_by(-.q_value) | .[] | select(.status == "active") | "Q:\(.q_value) | \(.feel) | \(.intent) → \(.file)"'
```

## Requirements

- OpenClaw (any version)
- `jq` (for search script)
- No other dependencies

## How It Works With memory_search

templates/skill.md

# SKILL: Skill Name

## Trigger
Keywords or phrases that should activate this skill

## Prerequisites
- What needs to be true before executing

## Procedure
1. Step one
2. Step two
3. Step three

## Cautions
- Things to watch out for

## Metrics
- Success rate: X% (N/N)
- Avg duration: Xs
- Q-value: X.XX
- Promoted: YYYY-MM-DD
- Sources: ep_YYYYMMDD_NNN, ep_YYYYMMDD_NNN, ep_YYYYMMDD_NNN

_meta.json

{
  "ownerId": "kn70hcm6kss09g9b4pe5rq3ybd80qp15",
  "slug": "guava-memory",
  "version": "1.0.0",
  "publishedAt": 1770809992167
}

templates/episode.md

# EP-TEMPLATE: Short task description

## Intent
What you were trying to accomplish

## Context
- domain: relevant area (e.g., note-api, deployment, config)
- tools: what tools/commands used
- precondition: what needed to be true before starting

## Experience

### ✅ Success Pattern
1. First step
2. Second step
3. Third step

### ❌ Failure Pattern
- What you tried that didn't work
- Why it failed

### 💡 Key Insight
- The most important thing you learned

## Utility
- reward: 0.0-1.0
- q_value: 0.0-1.0
- confidence: 0.0-1.0
- feel: flow | grind | frustration | eureka
- updated: YYYY-MM-DDTHH:MM:SS+TZ
- update_count: 1

## Tags
tag1, tag2, tag3

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Machine-readable data

The same record, as JSON, for agents and crawlers.

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}

Record generated Oct 9, 2026.

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