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๐ dreaming-optimizer
by
chongjie-ran
ยท GitHub โ
ยท v1.0.0
ยท MIT-0
68
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Install in OpenClaw
/install dreaming-optimizer
Description
Optimizes memory entries using LLM scoring, semantic deduplication, fact tagging, and writes consolidated summaries to persistent storage.
README (SKILL.md)
๐ dreaming-optimizer
Version: 1.0.0
Skill ID:dreaming-optimizer
Status: Ready for Development
Quick Reference
| ้กน็ฎ | ๅ ๅฎน |
|---|---|
| ๆ ธๅฟๅ็ | OpenClaw Dreaming REMๅ ญๆญฅ่ฎฐๅฟๆดๅ๏ผๆด็โ่ฏๅโๅป้โๆๆ โๆไบคโๆ่ฆ๏ผ |
| ไธปๅ ฅๅฃ | bin/optimize.sh |
| ไพ่ต | OpenClaw v2026.4.9+, tiktoken, sqlite3 |
Features (MVP)
- Entry scorer โ LLM-based priority scoring (0โ100)
- Deduplication โ Semantic similarity merge against existing memories
- Fact tagger โ Label as fact/opinion/preference/context
- Commit writer โ Write optimized entries to persistent memory
- Dreaming summary โ Traceable REM consolidation report
- Configurable threshold โ Min score threshold (default: 70)
File Structure
dreaming-optimizer/
โโโ SKILL.md # This file
โโโ bin/
โ โโโ optimize.sh # Main entry point
โ โโโ score_entries.py # LLM-based priority scoring
โ โโโ deduplicate.py # Semantic deduplication
โ โโโ commit.py # Write to B-layer
โโโ scripts/
โ โโโ dreaming_summary.py
โโโ config/
โ โโโ default_threshold.yaml
โโโ README.md
Usage
# Manual invoke
dreaming-optimizer/bin/optimize.sh
# With custom threshold
dreaming-optimizer/bin/optimize.sh --threshold 80
Integration
- Reads from:
~/.openclaw/workspace/memory/YYYY-MM-DD.md - Writes to:
~/.openclaw/memory/\x3Cagent>.sqlite(B-layer) - Summary output:
~/.openclaw/workspace/memory/dreaming-summaries/
Pricing
| Tier | Price | Features |
|---|---|---|
| Free | $0 | 10 cycles/mo, 100 entries/cycle |
| Pro | $9.90/mo | Unlimited, dedup, backfill queue, Obsidian export |
Development
See: ``
Usage Guidance
This skill appears to do what it says: read your OpenClaw daily notes, score/deduplicate/tag them, and write results into the OpenClaw B-layer SQLite and summary files. Before installing or running: 1) Review and back up ~/.openclaw/memory/*.sqlite and your workspace/memory files โ the skill will create/modify the DB and write archives. 2) Note the metadata mismatch: SKILL.md and code reference Python packages (tiktoken, optional sentence-transformers) and a required OpenClaw version that are not declared in registry requirements; ensure your environment has the necessary packages or that you understand which features will be disabled. 3) If you plan to enable the LLM/embedding 'Pro' features, confirm whether they require API keys/network access and where those credentials would be stored. 4) If you are not comfortable with the skill reading/writing your personal notes, do not install it or run it in a sandbox first (use --dry-run or run scripts with test input).
Capability Analysis
Type: OpenClaw Skill
Name: dreaming-optimizer
Version: 1.0.0
The dreaming-optimizer bundle is a well-structured memory management tool designed to score, deduplicate, and archive agent memories within the OpenClaw ecosystem. The code follows security best practices, such as using yaml.safe_load in config_loader.py to prevent arbitrary code execution and parameterized SQL queries in blayer_client.py to mitigate SQL injection risks. The logic is transparent, extensively documented in DESIGN.md, and lacks any indicators of data exfiltration, malicious execution, or prompt injection.
Capability Assessment
Purpose & Capability
The name/description (memory scoring, deduplication, tagging, commit to persistent storage) aligns with the code and runtime instructions: scripts read ~/.openclaw/workspace/memory/*.md, score/deduplicate entries, and write to ~/.openclaw/memory/<agent>.sqlite and summary files. However, the registry metadata omits runtime dependency notes (SKILL.md and code mention tiktoken, OpenClaw v2026.4.9+, and optional sentence-transformers), which is an inconsistency between declared requirements and actual code expectations.
Instruction Scope
The SKILL.md and entry scripts explicitly instruct the agent to read daily note files from ~/.openclaw/workspace/memory and write/modify the B-layer SQLite DB and archive/summary files under ~/.openclaw. This is coherent with the skill's purpose (optimizing memories). There are no obvious instructions to access other system areas or to transmit data externally, but the skill will read potentially sensitive user notes and persist changes to the user's memory DB.
Install Mechanism
No install spec is provided (instruction-only), which is low risk in isolation. However, the skill bundle includes many Python scripts and a YAML config โ so although no installer runs, those code files will be executed when invoked. Also, SKILL.md/code list dependencies (tiktoken, optional sentence-transformers) that are not declared in registry metadata; if the agent environment lacks those packages some functionality (LLM-enhanced scoring, embeddings) may be disabled or cause runtime errors.
Credentials
The registry lists no required environment variables or credentials, and the code as provided does not contain obvious external API calls or secret retrieval. That said, scoring/embedding features in the design reference LLM/embedding libraries (tiktoken, sentence-transformers). If those Pro features are enabled in the future they could require API keys or network accessโthose credentials are not declared now. Currently requested permissions (read/write under ~/.openclaw) are proportional to the stated purpose.
Persistence & Privilege
The skill writes persistent state to ~/.openclaw/memory/<agent>.sqlite and creates archive/summary files under ~/.openclaw/workspace/memory/. It does not request always:true and does not attempt to modify other skills' configs. Persisting to the B-layer is appropriate for a memory optimization tool, but it will alter user data (inserting/updating DB rows), so backups are advisable before running.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install dreaming-optimizer - After installation, invoke the skill by name or use
/dreaming-optimizer - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of dreaming-optimizer.
- Automates REM six-step memory optimization: sorting, scoring, deduplication, tagging, committing, and summarizing.
- Supports LLM-based scoring (0โ100) with configurable thresholds.
- Semantic deduplication to avoid redundant entries.
- Fact/opinion/preference/context tagging for each memory entry.
- Outputs traceable summaries after each optimization cycle.
- Integrates with OpenClaw workspace and persistent agent memory.
Metadata
Frequently Asked Questions
What is ๐ dreaming-optimizer?
Optimizes memory entries using LLM scoring, semantic deduplication, fact tagging, and writes consolidated summaries to persistent storage. It is an AI Agent Skill for Claude Code / OpenClaw, with 68 downloads so far.
How do I install ๐ dreaming-optimizer?
Run "/install dreaming-optimizer" in the OpenClaw or Claude Code chat to install it in one step โ no extra setup required.
Is ๐ dreaming-optimizer free?
Yes, ๐ dreaming-optimizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does ๐ dreaming-optimizer support?
๐ dreaming-optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created ๐ dreaming-optimizer?
It is built and maintained by chongjie-ran (@chongjie-ran); the current version is v1.0.0.
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