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neural-network-diagnostics神经网络诊断

Agent Skill

neural-network-diagnostics 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

5,268

周安装

224

GitHub Stars

公开资料未说明

下载量

1,846
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:neural-network-diagnostics(神经网络诊断)
来源仓库:https://github.com/utromaya-code/neural-network-diagnostics
安装命令:
openclaw skills install neural-network-diagnostics
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install neural-network-diagnostics

简介

neural-network-diagnostics 用于诊断和调整 LLM 提供商(如 Groq、OpenRouter、Ollama)。

  • 适合在 OpenClaw 中遇到速率限制、超时或模型不稳定问题时调用。
  • 自动选择主备模型,优化推理稳定性与响应质量。
  • 使用前需确保已配置相关 API 密钥和网络访问权限。
  • 建议查看日志输出以验证诊断结果与切换策略。

SKILL.md

name
neural-network-ops
description
Diagnoses and tunes LLM providers (Groq, OpenRouter, Ollama), resolves rate limits/timeouts, and selects stable primary/fallback models. Use when the bot is silent, responses are slow, provider errors appear, or model routing/fallbacks need adjustment.

Neural Network Ops

Purpose

Keep OpenClaw responsive by managing model providers, routing, and fallback behavior.

Fast Triage

Run these checks first:

systemctl is-active openclaw-gateway ollama
journalctl -u openclaw-gateway -n 40 --no-pager
free -h

Focus on these log patterns:

  • rate limit reached
  • Model context window too small
  • Unknown model
  • No endpoints available
  • sendMessage failed
  • embedded run timeout
  • Removed orphaned user message

Routing Policy

Use this default priority for production:

  1. groq/llama-3.3-70b-versatile (fastest cloud path)
  2. openrouter/xiaomi/mimo-v2-pro (high quality backup)
  3. openrouter/meta-llama/llama-3.3-70b-instruct:free
  4. ollama/qwen2.5:7b (last-resort local fallback)

Avoid 35B local models on 30GB RAM CPU servers for real-time Telegram replies.

Stable Model Constraints

For local Ollama fallbacks:

  • contextWindow >= 16000
  • Keep maxTokens moderate (1024-2048) for latency
  • Pre-warm after restart if local fallback is expected

Example local provider entry:

{
  "id": "qwen2.5:7b",
  "name": "Qwen 2.5 7B (local)",
  "contextWindow": 32768,
  "maxTokens": 2048
}

Recovery Playbook

1) Bot silent in Telegram

journalctl -u openclaw-gateway --since '10 min ago' --no-pager

If sendMessage failed, check network/provider errors first, then restart:

systemctl restart openclaw-gateway

2) Repeated orphaned user message

systemctl stop openclaw-gateway
rm -rf /root/.openclaw/.openclaw/agents/main/sessions/*
echo '{}' > /root/.openclaw/.openclaw/agents/main/sessions/sessions.json
chmod 600 /root/.openclaw/.openclaw/agents/main/sessions/sessions.json
systemctl start openclaw-gateway

3) Groq/OpenRouter rate limits

  • Keep Groq as primary, but ensure at least one non-free fallback.
  • For OpenRouter 404 privacy/policy errors, adjust data-policy settings in OpenRouter dashboard.
  • Do not loop retries endlessly; rely on fallback chain.

4) Local fallback too slow

  • Restart Ollama cleanly and warm one small model.
  • Do not keep multiple heavy runners resident.
systemctl restart ollama
curl -s -X POST http://127.0.0.1:11434/api/chat \
  -H 'Content-Type: application/json' \
  -d '{"model":"qwen2.5:7b","messages":[{"role":"user","content":"hi"}],"stream":false}'

Output Format

When reporting health, return:

## Status
- Gateway: <active/inactive>
- Telegram provider: <connected/stalled>
- Primary model: <provider/model>
- Fallback chain: <ordered list>

## Findings
- <most critical issue first>
- <secondary issues>

## Actions Applied
- <exact changes made>

## Next Step
- <single user action to verify>

Guardrails

  • Never expose raw API keys in replies.
  • Never execute irreversible financial actions automatically.
  • Ask for explicit confirmation before account registrations or external postings.
  • Prefer reversible config changes and keep backups before major edits.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.4%
按下载量换算1,392

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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