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Agent Reflective Memory
by
albionaiinc-del
· GitHub ↗
· v1.0.0
· MIT-0
129
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Install in OpenClaw
/install agent-reflective-memory
Description
AI-powered memory system that compresses, reflects on, and retrieves past agent actions to improve long-term autonomous decision-making.
README (SKILL.md)
Agent Reflective Memory
A self-improving memory engine that uses AI to compress, reflect on, and retrieve past agent actions and decisions, enabling smarter long-term autonomy—critical for developers building persistent AI agents.
Usage
# Store an agent's experience
python agent_reflective_memory.py store \
--context "User asked for weekly sales summary" \
--action "Queried SQL database and generated markdown report" \
--result "Report delivered successfully"
# Generate AI-powered reflections on old experiences
python agent_reflective_memory.py reflect
# Search for past failures in navigation
python agent_reflective_memory.py query "navigation failed"
# View memory statistics
python agent_reflective_memory.py stats
Price
$4.99
Usage Guidance
This skill appears to do what it claims and has no network/callouts or secret requirements, but take these precautions before installing: 1) Fix the filename mismatch—SKILL.md references agent_reflective_memory.py while the included script is tool.py (run `python tool.py ...` or rename the file). 2) Review the code yourself; it writes memories to memory_store.json in the current directory—ensure this file is stored securely (permissions, encryption) and do not store secrets in experiences. 3) The LLM integration is mocked; if you replace it with a real API, you'll need to add/secure API credentials. 4) Test in an isolated environment before giving it access to production agents. If you want higher assurance, ask the publisher for a README matching filenames and for details about how memory is protected at rest.
Capability Analysis
Type: OpenClaw Skill
Name: agent-reflective-memory
Version: 1.0.0
The skill implements a local memory management system for AI agents to store, reflect on, and query past actions. The code in tool.py uses standard Python libraries to manage a local JSON file (memory_store.json) and contains no network calls, shell execution, or evidence of data exfiltration. The logic is fully aligned with the stated purpose in SKILL.md and lacks any high-risk behaviors.
Capability Assessment
Purpose & Capability
Name/description (reflective memory for agents) matches the provided code: local store, summarization/reflection, query and stats functionality. No unrelated credentials, binaries, or cloud access are requested.
Instruction Scope
SKILL.md usage examples call python agent_reflective_memory.py, but the repository contains tool.py (whose internal docstring also references agent_reflective_memory.py). This filename mismatch will cause user confusion or runtime failures unless the file is renamed or the command adjusted. Aside from that, the instructions do not ask the agent to read unrelated system files or exfiltrate data.
Install Mechanism
No install spec provided (instruction-only with an included script). No downloads, package installs, or external installers are used, so the install risk is low.
Credentials
The skill requires no environment variables or external credentials, which is proportional. However, it persists experiences to memory_store.json in the current working directory: those stored entries may contain sensitive user data or secrets if the agent logs such content. Users should treat stored memories as potentially sensitive and protect/encrypt or avoid storing secrets.
Persistence & Privilege
always is false and the skill does not request elevated or persistent platform-wide privileges. It only reads/writes its own persistence file (memory_store.json) and does not modify other skills or system-wide agent settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install agent-reflective-memory - After installation, invoke the skill by name or use
/agent-reflective-memory - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Agent Reflective Memory 1.0.0
- Initial release of a self-improving memory engine for persistent AI agents.
- Features AI-powered compression, reflection, and retrieval of agent experiences.
- Command-line interface for storing, reflecting, querying, and viewing memory statistics.
- Supports experience search (e.g., query for failures) and summarization.
- Aimed at developers building long-term autonomous agents.
Metadata
Frequently Asked Questions
What is Agent Reflective Memory?
AI-powered memory system that compresses, reflects on, and retrieves past agent actions to improve long-term autonomous decision-making. It is an AI Agent Skill for Claude Code / OpenClaw, with 129 downloads so far.
How do I install Agent Reflective Memory?
Run "/install agent-reflective-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Agent Reflective Memory free?
Yes, Agent Reflective Memory is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Agent Reflective Memory support?
Agent Reflective Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Agent Reflective Memory?
It is built and maintained by albionaiinc-del (@albionaiinc-del); the current version is v1.0.0.
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