everything-claude-code-zh is a Chinese translation of a collection of configurations for Claude Code and other AI coding agents. It provides agents, skills, hooks, commands, rules, and MCP configurations intended to support development workflows such as memory persistence, security scanning, evaluation, and research-first work. The catalogue includes commands, skills, agents, instructions, and a plugin from this configuration set.
Borrowing it
Nothing to install: this file belongs to xu-xiang/everything-claude-code-zh. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xu-xiang/everything-claude-code-zh/main/.agents/skills/market-research/SKILL.mdgit clone --depth 1 https://github.com/xu-xiang/everything-claude-code-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xu-xiang/everything-claude-code-zh/market-research)<a href="https://agentmods.dev/skills/xu-xiang/everything-claude-code-zh/market-research"><img src="https://agentmods.dev/badge/skills/xu-xiang/everything-claude-code-zh/market-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xu-xiang/everything-claude-code-zh/market-research"><img src="https://agentmods.dev/badge/skills/xu-xiang/everything-claude-code-zh/market-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.00742 |
| Opus 5 | $0.00033 | $0.00371 |
| Sonnet 5 | $0.00013 | $0.00148 |
| Haiku 4.5 | $0.00007 | $0.00074 |
Grade A, and why
market-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
市场研究 (Market Research)
提供支持决策的研究，而非流于形式的研究报告。
激活时机 (When to Activate)
- 研究市场、类别、公司、投资者或技术趋势时。
- 构建 TAM/SAM/SOM（总目标市场/可服务市场/可获得市场）估算时。
- 比较竞争对手或相邻产品时。
- 在对外接触前准备投资者档案（Investor Dossiers）时。
- 在构建产品、注资或进入市场前对逻辑假设进行压力测试时。
研究标准 (Research Standards)
- 每个重要论点都必须有来源引用。
- 优先使用近期数据，并标注陈旧数据。
- 包含对立证据（Contrarian Evidence）和下行案例（Downside Cases）。
- 将发现转化为决策依据，而不仅仅是摘要。
- 清晰区分事实（Fact）、推论（Inference）和建议（Recommendation）。
常用研究模式 (Common Research Modes)
投资者 / 基金尽职调查 (Investor / Fund Diligence)
收集：
- 基金规模、阶段和典型单笔投资额（Check Size）。
- 相关的投资组合公司（Portfolio Companies）。
- 公开的投资逻辑（Thesis）和近期活动。
- 该基金是否匹配的原因。
- 任何明显的风险信号（Red Flags）或不匹配项。
竞争分析 (Competitive Analysis)
收集：
- 产品实际情况，而非营销文案。
- 若公开，收集融资和投资者历史。
- 若公开，收集增长指标（Traction Metrics）。
- 分销渠道和定价线索。
- 优势、劣势和定位差距（Positioning Gaps）。
市场规模测算 (Market Sizing)
使用：
- 来自报告或公开数据集的自上而下（Top-down）估算。
- 基于现实获客假设的自下而上（Bottom-up）合理性检查。
- 为逻辑中的每一个跨跃提供明确的假设。
技术 / 供应商研究 (Technology / Vendor Research)
收集：
- 工作原理。
- 权衡（Trade-offs）和采用信号。
- 集成复杂性。
- 锁定风险（Lock-in）、安全、合规及运营风险。
输出格式 (Output Format)
默认结构：
- 执行摘要 (Executive Summary)
- 核心发现 (Key Findings)
- 影响分析 (Implications)
- 风险与注意事项 (Risks and Caveats)
- 建议 (Recommendation)
- 来源 (Sources)
质量把关 (Quality Gate)
在交付前确认：
- 所有数字均有来源或标记为估算。
- 旧数据已被标注。
- 建议内容逻辑严密，源自现有证据。
- 已包含风险和反面论点。
- 输出内容能让决策变得更轻松。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 76 lines · 66 tokens per session scan A f567f5ef7c90
market-research is a skill published in the GitHub repository xu-xiang/everything-claude-code-zh (1,941 stars, last pushed 6mo ago), licensed MIT. It adds 66 tokens to every session and 742 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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