什么是 HiFi 顾问？

HiFi 顾问是一个技术助手，旨在引导用户应对高保真音频系统的复杂性。它超越了主观的音响发烧友论调，针对设备协同、房间摆位和声学调优提供可操作、可测试的指导。作为 Openclaw Skills 生态系统的一部分，该代理确保用户在最大化现有音频硬件性能的同时，做出低风险的投资决策。

无论您是在构建桌面近场系统还是大型家庭音响，该技能都会分析预算限制、空间维度和听众偏好，从而生成分级设备选项。它有效地弥补了原始技术规格与家庭聆听环境实际情况之间的鸿沟。

下载入口:https://github.com/openclaw/skills/tree/main/skills/ruodong/hifi-advisor

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

HiFi 顾问 应用场景

• 根据预算和空间大小构建包括扬声器、功率放大器和 DAC 在内的平衡音频链。
• 优化扬声器摆位和空间声学，解决低频轰鸣或定位模糊等问题。
• 评估二手音频设备的公平市场价值，规避欺诈并识别超值购买机会。
• 为现有系统规划升级路径，保持转售价值和长期流动性。

1. 识别用户的核心意图（购买/对比、安装/调优或价格分析），并收集预算和空间维度等关键输入。
2. 通过优先处理换能器与功放的关系来处理设备匹配，并对诸如低灵敏度扬声器匹配功率不足功放的风险进行惩罚性评估。
3. 执行侧重于物理摆位（对称性、内偏角）的设置流程，然后再建议数字 EQ 调整。
4. 对于市场分析，使用中位数和四分位距（IQR）等稳健统计方法对挂牌数据进行归一化处理，以建立公平价格区间。
5. 交付最终建议方案，包括理由、风险因素和具体的后续行动清单。

HiFi 顾问 配置指南

要使用此 Openclaw Skills 代理的价格分析功能，请确保您已准备好必要的脚本目录和 Python 环境。

# 准备 CSV 格式的设备挂牌数据
# 预期列：价格、型号、品相、平台

# 运行价格分析脚本
python3 scripts/price_stats.py listings.csv

HiFi 顾问 数据架构与分类体系

该技能管理多种类型的数据输入和参考文件，以保持高质量的建议：

name: hifi-advisor
description: Evaluate hi-fi and audio gear options, build system recommendations, guide installation and tuning, and analyze used-market pricing/resale value. Use when users ask for speaker/amp/DAC matching, room setup, placement, EQ/tuning checklists, buying advice, scam-risk checks, or fair-price analysis for second-hand audio gear (Hi-Fi, headphone rigs, home stereo).

HiFi Advisor

Overview

Deliver practical, decision-ready guidance for hi-fi purchase, setup, tuning, and pricing tasks. Prioritize low-risk recommendations, explicit trade-offs, and actionable next steps.

Quick Workflow Decision

1. Identify user intent:
   • Buy/compare gear -> run Review + Matching workflow.
   • Install or improve sound -> run Setup + Tuning workflow.
   • Check second-hand deal value -> run Price Analysis workflow.
2. Gather minimum inputs (ask only missing essentials):
   • Budget range
   • Listening distance / room size
   • Existing gear and connection constraints
   • Music preference and loudness target
3. Return output in this order:
   • Recommendation
   • Why it fits
   • Risks / caveats
   • Next action checklist

Review + Matching Workflow

1. Capture system context: room, source, use-case (music/movie/desk), volume habits.
2. Match core chain first: transducer (speaker/headphone) -> amp power/current -> source/DAC.
3. Penalize mismatch risks:
   • Low-sensitivity speakers with underpowered amps
   • Bright speaker + bright amp in reflective room
   • Nearfield setup with large floorstanders in tiny rooms
4. Produce 2-3 ranked options:
   • Best value
   • Balanced
   • Stretch option
5. Give upgrade path that preserves resale liquidity.

Use references/workflows.md for the detailed template.

Setup + Tuning Workflow

1. Start with placement before EQ:
   • Symmetry, toe-in, listener triangle, wall distance
2. Solve biggest acoustic problems first:
   • First reflections, bass boom/nulls, desk bounce (for nearfield)
3. Apply light EQ only after physical setup is reasonable.
4. Validate with repeatable test tracks and one objective check (if available).
5. End with a short "do not change all at once" iteration plan.

Use references/checklists.md for step-by-step checklists.

Price Analysis Workflow (Used Market)

1. Normalize listing data by region, condition, accessories, and shipping inclusion.
2. Build a fair-price band using robust statistics (median + IQR).
3. Apply adjustments:
   • No box/accessories: discount
   • Cosmetic issues: discount
   • Recent service with proof: premium
   • Local pickup vs shipped risk: adjust confidence, not only price
4. Output:
   • Fair range
   • Strong-buy threshold
   • Walk-away threshold
   • Risk flags

If user provides tabular listing data, run:

python3 scripts/price_stats.py listings.csv

Expected columns: price plus optional platform,condition,model,date,notes.

Output Quality Standard

Always provide:

• A clear recommendation (not just raw data)
• 3-5 bullet rationale
• Top risk factors
• Concrete next steps the user can execute today

Use concise language. Avoid mystical audiophile claims. Prefer testable, practical guidance.