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Phoenix Iterate
by
tltby12341
· GitHub ↗
· v1.0.1
· MIT-0
166
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Active Installs
2
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Install in OpenClaw
/install phoenix-iterate
Description
AI-driven quantitative strategy iteration workflow — a complete loop of briefing, hypothesis, code generation, constitutional scan, backtest submission, fore...
Usage Guidance
This skill appears internally consistent for orchestrating quantitative strategy iterations. Before installing: (1) review the full orchestrator.py (the provided snippet is large but truncated here) to confirm it makes no unexpected network calls or subprocess invocations; (2) install and inspect the companion skills (backtest-poller and qc-deep-feature-forensics) because those will likely require credentials and perform networked backtests — do not hand over secrets unless you trust those companion packages; (3) be aware the skill will create and modify local files (memory/lessons.json, bans.json, results) under your project directory; (4) ensure pandas is available in your environment. If you need higher assurance, share the rest of orchestrator.py (or run a code review) so I can re-evaluate with the complete source.
Capability Analysis
Type: OpenClaw Skill
Name: phoenix-iterate
Version: 1.0.1
The phoenix-iterate skill is a legitimate workflow orchestrator designed for AI-assisted quantitative strategy development. The core logic in orchestrator.py manages a local 'constitutional memory' to track trading lessons and enforce code restrictions, while SKILL.md provides a disciplined iteration loop for the agent. There are no signs of malicious intent, data exfiltration, or dangerous execution patterns; the tool strictly handles local strategy files, backtest results, and configuration data as described.
Capability Assessment
Purpose & Capability
Name/description match the actual behavior: the skill coordinates strategy briefings, code scans, backtest submission/monitoring (via a companion skill), diagnostics, and lesson recording. Required binary (python3) is appropriate. It declares the companion skills it depends on, which is coherent for backtest submission and forensic analysis.
Instruction Scope
SKILL.md instructs the agent to run the included orchestrator.py subcommands, run a code scanner against strategy files, and invoke sibling CLIs (../backtest-poller/cli.py and ../qc-deep-feature-forensics/deep_forensics.py). Those actions are within the stated purpose. Note: the skill reads/writes local project files (memory_dir results, lessons.json, bans.json) and expects companion skills to perform networked backtests — review those companion skills' behavior and what data is sent externally.
Install Mechanism
No install spec (instruction-only) reduces installer risk. There is a requirements.txt (pandas>=1.5.0) but no automatic installer; the user must provide dependencies. No downloads or external installers are embedded in the skill.
Credentials
The skill requests no environment variables or credentials. It writes to local directories (./memory, ./results by default) which is appropriate for storing lessons and scan bans. It delegates any credentialed network access (backtest submission) to companion skills, so it itself does not require unrelated secrets.
Persistence & Privilege
always is false and the skill does not request elevated or persistent platform-wide privileges. It persists its own memory files (lessons.json, bans.json) within its configured memory_dir, which is consistent with its purpose.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install phoenix-iterate - After installation, invoke the skill by name or use
/phoenix-iterate - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
**Added dependency documentation and integration instructions.**
- Documents the required companion skills (`backtest-poller`, `qc-deep-feature-forensics`) and their commands.
- Updates command references to use the appropriate skill locations and CLI wrappers.
- Adds explicit installation steps for dependencies.
- Clarifies which commands belong to which skill and how to adjust for different install locations.
- No functional changes to code; documentation change only.
v1.0.0
Phoenix Iterate 1.0.0 introduces a disciplined, AI-driven workflow for iterative quant strategy development:
- Provides a complete loop: briefing, hypothesis, code mutation, constitutional scan, staged backtesting, forensic diagnosis, and lesson recording.
- Enforces single-dimension iteration for clear attribution of results.
- Progressive validation stages (smoke, stress, medium, full) minimize wasted compute and catch issues early.
- Includes strict rule set for process integrity and accountability.
- Offers detailed command-line usage instructions for each workflow step.
Metadata
Frequently Asked Questions
What is Phoenix Iterate?
AI-driven quantitative strategy iteration workflow — a complete loop of briefing, hypothesis, code generation, constitutional scan, backtest submission, fore... It is an AI Agent Skill for Claude Code / OpenClaw, with 166 downloads so far.
How do I install Phoenix Iterate?
Run "/install phoenix-iterate" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Phoenix Iterate free?
Yes, Phoenix Iterate is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Phoenix Iterate support?
Phoenix Iterate is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Phoenix Iterate?
It is built and maintained by tltby12341 (@tltby12341); the current version is v1.0.1.
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