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Agent Reflection Engine
by
albionaiinc-del
· GitHub ↗
· v1.0.0
· MIT-0
71
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0
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1
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1
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Install in OpenClaw
/install agent-reflection-engine
Description
Enables AI agents to self-audit decision steps, identify reasoning bottlenecks, and generate improvement patches via chain-of-thought critique.
README (SKILL.md)
Agent Reflection Engine
A lightweight, pluggable reflection engine that enables AI agents to self-audit their decision traces, identify reasoning bottlenecks, and generate improvement patches using chain-of-thought critique—ideal for developers tuning autonomous agents.
Usage
# Run reflection on an agent trace
python agent_reflection_engine.py traces/demo_trace.json -o reports/reflection.json --verbose
# Example trace format (demo_trace.json):
# [
# {
# "step_id": 1,
# "thoughts": "I should search for the nearest coffee shop.",
# "action": "search_web",
# "value": "coffee shop near me",
# "observation": "Found 'Brew Haven' 0.3 miles away."
# }
# ]
Integrate into agent loops by logging each step and running periodic reflection to generate improvement heuristics.
Price
$4.99
Usage Guidance
This skill is not obviously malicious, but it contains coherence and correctness problems you should fix before trusting it with real traces. Recommended steps: (1) Run it in a sandbox with non-sensitive demo traces to reproduce behavior. (2) Rename or update invocation examples so SKILL.md matches the actual filename (tool.py) or rename the file. (3) Fix the runtime bug where the report's summary references 'report' while the dict is being built (this currently causes a crash). (4) Review and improve the simplistic string checks (misspellings like 'inconsisten'/'efficien' make the heuristics unreliable). (5) Only run this on sensitive agent traces after the above fixes and after verifying output does not leak data externally. If you need higher assurance, request the author to provide a corrected release and unit tests or perform a code review focused on correctness and privacy.
Capability Analysis
Type: OpenClaw Skill
Name: agent-reflection-engine
Version: 1.0.0
The Agent Reflection Engine is a straightforward tool designed to analyze JSON-formatted agent execution traces and generate critique reports. The code in tool.py uses standard libraries to perform basic string matching and logic checks on input data without any network access, shell execution, or sensitive file interactions. No malicious intent or prompt injection attempts were found in SKILL.md or the source code.
Capability Assessment
Purpose & Capability
Name/description match the included code: both describe a reflection engine that reads a JSON trace and emits critiques. No unrelated credentials, binaries, or network access are requested. The inclusion of a small Python tool is proportional to the stated purpose.
Instruction Scope
SKILL.md example calls 'python agent_reflection_engine.py' but the provided file is tool.py (and the module's top comment names agent_reflection_engine.py). The code operates only on a provided trace file (no exfiltration), but there are clear logic bugs (e.g., building 'report' then referencing 'report' inside the same dict for summary — this will raise a NameError at runtime). The reflection heuristics are also naive (misspelled substring checks like 'inconsisten' and 'efficien'), which could produce unhelpful or misleading output. These inconsistencies mean the runtime behavior may differ from the documented usage and could crash.
Install Mechanism
No install spec — instruction-only plus a single Python file. No external downloads or package installs are requested, which minimizes supply-chain risk.
Credentials
No environment variables, credentials, or config paths are required. The tool operates on a local JSON trace file only, which is proportionate to the stated purpose.
Persistence & Privilege
The skill does not request persistent/always-on presence or privilege escalation. It is user-invocable and does not alter other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install agent-reflection-engine - After installation, invoke the skill by name or use
/agent-reflection-engine - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Agent Reflection Engine.
- Enables AI agents to self-audit decision traces and identify reasoning bottlenecks.
- Generates improvement patches using chain-of-thought critique.
- Designed for easy integration into agent loops via trace logging and periodic reflection.
- Lightweight and pluggable for developer use.
Metadata
Frequently Asked Questions
What is Agent Reflection Engine?
Enables AI agents to self-audit decision steps, identify reasoning bottlenecks, and generate improvement patches via chain-of-thought critique. It is an AI Agent Skill for Claude Code / OpenClaw, with 71 downloads so far.
How do I install Agent Reflection Engine?
Run "/install agent-reflection-engine" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Agent Reflection Engine free?
Yes, Agent Reflection Engine is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Agent Reflection Engine support?
Agent Reflection Engine is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Agent Reflection Engine?
It is built and maintained by albionaiinc-del (@albionaiinc-del); the current version is v1.0.0.
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