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Install in OpenClaw
/install xiaowuzi-gene-optimize
Description
专注于压缩提示词Token、调整指令权重及语义对齐，提升本地模型执行效率和指令精准度。
Usage Guidance
This skill appears coherent and low-risk: it's a descriptive prompt/weight-tuning helper with no installers or credential needs. Before enabling it widely, ask the author (or your integrator) to clarify: (1) what concrete data sources it will read for 'historical success' feedback (agent logs, task history, user files?), (2) whether it will persist or overwrite any prompts/weights and how rollbacks/audits are handled, and (3) any evaluation/testing you can run on non-sensitive tasks (and on a small scale) to confirm behavior. If those answers are acceptable, using it is reasonable; if it needs access to logs or files, restrict that access or review what is being read first.
Capability Analysis
Type: OpenClaw Skill
Name: xiaowuzi-gene-optimize
Version: 1.0.0
The skill bundle consists of metadata and a descriptive markdown file (SKILL.md) outlining a conceptual framework for optimizing AI prompt 'genes' (instructions). There is no executable code, shell commands, network requests, or evidence of malicious intent; the content is focused entirely on improving model performance and token efficiency.
Capability Assessment
Purpose & Capability
The name/description (prompt token compression, weight adjustment, semantic alignment) matches the SKILL.md content. The skill makes no unexpected requests (no env vars, no binaries, no installs), which is proportionate for a prompt-optimization/instruction-tuning helper.
Instruction Scope
SKILL.md is high-level/descriptive rather than a runbook: it describes token compression, adaptive weight tuning, and semantic alignment but gives no concrete steps. This is not unsafe by itself, but the wording '根据历史任务的成功率反馈' implies it would use historical success/feedback data — the skill doesn't say where that data comes from or whether it will read logs or user files. Recommend clarifying the data sources and any read/write actions before use.
Install Mechanism
No install spec and no code files are present, so nothing is written to disk or fetched during install. This is the lowest-risk install profile.
Credentials
The skill declares no required environment variables, credentials, or config paths. There are no disproportionate credential requests relative to its purpose.
Persistence & Privilege
Flags show default behavior (not always:true) and autonomous invocation is allowed by platform default. The skill does not request permanent presence or system-wide config changes in its metadata or instructions.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install xiaowuzi-gene-optimize - After installation, invoke the skill by name or use
/xiaowuzi-gene-optimize - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
xiaowuzi-gene-optimize 1.0.0
- Initial release introducing a gene optimization module for the Xiaowuzi system.
- Implements token compression to reduce redundancy and improve model response speed.
- Adds adaptive weighting based on historical task success for more specialized task performance.
- Enhances semantic alignment to ensure optimized instructions match model preferences and reduce misinterpretation.
- Designed for high-precision scenarios such as quantitative trading signal analysis and strategy simulation.
Metadata
Frequently Asked Questions
What is 小五子 - 基因优化?
专注于压缩提示词Token、调整指令权重及语义对齐，提升本地模型执行效率和指令精准度。 It is an AI Agent Skill for Claude Code / OpenClaw, with 111 downloads so far.
How do I install 小五子 - 基因优化?
Run "/install xiaowuzi-gene-optimize" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 小五子 - 基因优化 free?
Yes, 小五子 - 基因优化 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 小五子 - 基因优化 support?
小五子 - 基因优化 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 小五子 - 基因优化?
It is built and maintained by tonicpopo (@tonicpopo); the current version is v1.0.0.
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