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Bounded Memory
by
canmaxfire
· GitHub ↗
· v1.1.1
· MIT-0
114
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Install in OpenClaw
/install bounded-memory
Description
Provides fast full-text search of OpenClaw session histories with optional LLM summarization for recalling past conversations and decisions.
README (SKILL.md)
Bounded Memory
Gives your OpenClaw AI agent a perfect memory — it can recall anything you've ever discussed, even from months ago.
What It Does
Without this skill: each OpenClaw session starts fresh. The AI forgets everything.
With this skill: ask things like:
- "Did we discuss X before?"
- "What did we decide about Y?"
- "Find that conversation from last month"
Privacy Design
| What runs | How |
|---|---|
| Search indexing | ✅ 100% offline — SQLite only |
| Search execution | ✅ 100% offline — no network calls |
| LLM summarization | ⚠️ Opt-in only — use --llm flag to enable |
No external API calls by default. The --llm flag (disabled by default) sends snippets to your configured LLM for summarization — only when you explicitly ask for it.
Quick Start
# Index your conversations (first time)
python3 skills/session-search/scripts/index-sessions.py --agent main
# Search (fully offline)
python3 skills/session-search/scripts/search-sessions.py "what did we decide about the logo design"
# Search with AI summary (opt-in)
python3 skills/session-search/scripts/search-sessions.py "question" --llm
What It Solves
| Problem | Without | With Bounded Memory |
|---|---|---|
| "I asked this before but can't remember" | AI has no idea | Instant recall |
| "What did we decide in that meeting?" | Forgot | Searches all sessions |
| "Did I mention this before?" | No way to know | Searches everything |
Example
You: "Search our conversations about the robot project"
→ Found 3 discussions:
1. [Last week] We discussed the design direction...
2. [2 weeks ago] You asked about pricing...
3. [Last month] The AI suggested adding...
Usage Guidance
This skill appears to do what it claims: index your OpenClaw session .jsonl files into a local SQLite FTS5 DB and search them, with optional LLM summaries only when you pass --llm. Before installing/running: (1) verify the skill source (registry metadata shows unknown/origin inconsistencies in README GitHub links); (2) inspect ~/.openclaw/openclaw.json to see which API keys/providers are stored (the script will use the first apiKey it finds when you enable --llm); (3) only use --llm if you consent to sending matched conversation snippets to the external endpoint (the code calls https://api.minimax.chat/v1); (4) consider where the DB will be stored (SESSION_SEARCH_DB_DIR or the skill db folder) and remove it if you want to revoke the indexed data. If provenance is important, confirm the repository and maintainer identity before installing.
Capability Tags
Capability Assessment
Purpose & Capability
The skill claims to index and search OpenClaw session histories and the shipped scripts read ~/.openclaw/agents/*/sessions/*.jsonl, build an SQLite FTS5 DB, and search it. Access to agent session files and an on-disk DB is required and present. The optional LLM summary path that reads an API key from ~/.openclaw/openclaw.json or env vars is consistent with the described opt-in summarization feature.
Instruction Scope
SKILL.md instructs running the included index and search scripts. The scripts only read session files, write a local SQLite DB, and (only when --llm is used) send selected snippets to an external LLM endpoint. There is no instruction to read unrelated system files or exfiltrate data by default. Note: indexing can enumerate all agents when run with --all-agents.
Install Mechanism
No install spec is present (instruction-only); the scripts run as-is with Python and SQLite, which is proportional and low-risk. Nothing is downloaded or extracted by the skill installer.
Credentials
No required env vars are declared. The code optionally reads OPENCLAW_AGENTS_DIR and SESSION_SEARCH_DB_DIR to override paths (reasonable). For summarization it looks for an API key in ~/.openclaw/openclaw.json or env vars (MINIMAX_API_KEY, OPENAI_API_KEY). This is proportional to the optional LLM feature, but be aware it will pick the first provider apiKey present in your OpenClaw config — review that file so you know which key would be used when you enable --llm.
Persistence & Privilege
The skill does not request always:true and runs only when invoked. It writes its own DB file under the skill workspace (or overridden path) and does not modify other skills or global agent settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install bounded-memory - After installation, invoke the skill by name or use
/bounded-memory - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.1
Fix: LLM truly opt-in, remove sessions.db from git, add .gitignore
v1.1.0
Rewrite: plain language descriptions, user benefit focus instead of technical jargon
v1.0.4
Chore: convert all documentation to English
v1.0.3
Security: add transparency section, clarify LLM opt-in/out, declare API key access, fix doc inconsistencies
v1.0.2
Correct display name to Bounded Memory
v1.0.1
Fix: replace example queries with generic placeholders to prevent session data leakage
v1.0.0
Initial release: SQLite FTS5 session search, Hermes bounded-memory pattern for OpenClaw
Metadata
Frequently Asked Questions
What is Bounded Memory?
Provides fast full-text search of OpenClaw session histories with optional LLM summarization for recalling past conversations and decisions. It is an AI Agent Skill for Claude Code / OpenClaw, with 114 downloads so far.
How do I install Bounded Memory?
Run "/install bounded-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Bounded Memory free?
Yes, Bounded Memory is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Bounded Memory support?
Bounded Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Bounded Memory?
It is built and maintained by canmaxfire (@canmaxfire); the current version is v1.1.1.
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