Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add YangsonHung/awesome-agent-skills --skill conversation-json-to-md-cngit clone --depth 1 https://github.com/YangsonHung/awesome-agent-skillsWrote 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/yangsonhung/awesome-agent-skills/conversation-json-to-md-cn)<a href="https://agentmods.dev/skills/yangsonhung/awesome-agent-skills/conversation-json-to-md-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/conversation-json-to-md-cn/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/yangsonhung/awesome-agent-skills/conversation-json-to-md-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/conversation-json-to-md-cn.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 | $0.00036 | $0.00838 |
| Opus 5 | $0.00018 | $0.00419 |
| Sonnet 5 | $0.00007 | $0.00168 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
conversation-json-to-md-cn 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 12d 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
Conversation JSON 转 Markdown（中文）
Overview
将用户提供的聊天导出 JSON 转换为多个结构清晰的 Markdown 文件，并统一为问答结构。流程会按会话拆分文件，只保留用户与助手问答，保留回答中的 Markdown，并在导出后做一次命名和标题结构的二次整理。
何时使用
当用户有以下需求时使用本技能：
- 把一个对话导出 JSON 拆成多个
.md - 一个会话对应一个 Markdown 文件
- 只保留用户与助手问答内容
- 问题作为标题，回答统一为
回答 - 导出后再做一次命名和标题二次格式化
不要使用
以下场景不应使用本技能：
- 与 JSON 对话导出无关的普通文本改写
- 非会话数据结构处理任务
- 用户要的是语义总结而非结构化导出
使用说明
- 必须读取用户明确提供的输入文件路径，不假设默认文件名。
- 自动识别 JSON 结构并提取会话。
- 每个会话导出为一个 Markdown 文件。
- 仅保留用户/助手问答内容。
- 问答格式固定为：
## <问题文本>### 回答
- 保留回答正文的 Markdown，并将回答内部标题整体降级 1 级。
- 导出完成后执行一轮独立二次格式化检查与修正。
支持的输入结构
脚本可识别以下常见格式：
- DeepSeek/ChatGPT 类
mapping/root/children/fragments - Qwen 类
data[].chat.messages[]+content_list（优先phase=answer） - Claude 网页导出
list[{ name, chat_messages: [...] }] - 通用消息数组
messages/history/conversations/dialog/turns - 成对问答字段
question-answer、prompt-response、input-output
如果结构无法识别，停止并让用户提供样例片段，再扩展解析规则。
运行脚本
python3 scripts/convert_conversations.py \
--input /path/to/<用户提供>.json \
--output-dir /path/to/conversations_md \
--clean
输出格式（固定）
# <会话标题>
## <用户问题1>
### 回答
<助手回答 Markdown>
## <用户问题2>
### 回答
<助手回答 Markdown>
二次格式化流程（独立步骤）
导出后，对输出目录执行二次格式化：
- 文件名规范化：
- 保持“仅会话标题”命名
- 清理非法字符
- 重名补齐
(2)、(3)序号
- 标题结构规范化：
- 一级标题仅保留会话标题：
# <会话标题> - 每个问题必须是二级标题
- 每个回答必须是
### 回答
- 回答正文规范化：
- 保留 Markdown
- 内部标题降级 1 级，避免与外层结构冲突
- 结果复检：
- 发现不符合规则的文件时逐个修正后再交付
验证清单
- 导出文件数与识别到的会话数一致
- 文件名无随机后缀
- 文件中不出现
## REQUEST/## RESPONSE - 回答块统一为
### 回答 - Markdown 预览渲染正常
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.
- 12d ago First seen · 102 lines · 36 tokens per session scan A 786641d71c73
conversation-json-to-md-cn is a skill published in the GitHub repository YangsonHung/awesome-agent-skills (18 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 838 once invoked, about $0.0002 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.
Other skills, from other repositories
baoyu-youtube-transcript
A tool for downloading the written captions, subtitles, chapter information, speaker labels, and cover image from a YouTube video using its URL or ID.
pydicom
Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
treatment-plans
Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and…
venue-templates
Prepare journal manuscripts, conference papers, research posters, and grant documents using venue-specific formatting guidance and bundled LaTeX scaffolds. Use when selecting an official template, checking current page or anonymity rules, adapting academic writing to a venue, or inspecting a submission PDF.
xlsx
Create, edit, analyze, or convert Excel spreadsheets (.xlsx, .xlsm, .xltx) where the workbook file is the primary deliverable. Use for formulas, formatting, financial models, multi-sheet workbooks, and tabular cleanup exported to Excel. Also applies to .csv/.tsv when the user wants spreadsheet output. Do NOT use for…
outline
Search, read, and manage Outline wiki documents. Use when: (1) searching wiki for documentation, (2) reading wiki pages or articles, (3) listing wiki collections or documents, (4) creating or updating wiki content, (5) exporting documents as markdown. Works with any Outline wiki instance (self-hosted or cloud).