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-mdgit 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)<a href="https://agentmods.dev/skills/yangsonhung/awesome-agent-skills/conversation-json-to-md"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/conversation-json-to-md/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"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/conversation-json-to-md.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 | $0.00028 | $0.00708 |
| Opus 5 | $0.00014 | $0.00354 |
| Sonnet 5 | $0.00006 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
conversation-json-to-md 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conversation JSON To MD
Overview
Convert a user-provided chat-export JSON into multiple Markdown files with consistent Q/A formatting. The workflow keeps only user-assistant exchanges, writes one conversation per Markdown file, preserves answer Markdown, and runs a second pass to normalize filenames and heading structure.
When to Use
Use this skill when the user asks for:
- Splitting one JSON chat export into many
.mdfiles - One conversation per markdown file
- Keeping only question/answer content from user and assistant
- Renaming response sections to
Answer - Normalizing exported files with a second formatting pass
Do not use
Do not use this skill for:
- Plain text transformation that does not involve JSON chat exports
- Non-conversation JSON processing tasks
- Requests requiring semantic summarization instead of structural conversion
Instructions
- Read the input file path provided by the user. Do not assume default file names.
- Detect conversation/message structure automatically.
- Export one markdown file per conversation.
- Keep only user/assistant Q&A content.
- Format each Q/A block as:
## <question text>### Answer
- Preserve answer markdown and demote answer-internal heading levels by one level.
- Run an independent second-pass formatting check and fix naming/title structure before final delivery.
Supported Input Structures
The bundled script supports common export formats including:
- DeepSeek/ChatGPT-like mapping tree (
mapping/root/children/fragments) - Qwen-like exports (
data[].chat.messages[],content_listwithphase=answer) - Claude web export style (
list[{ name, chat_messages: [...] }]) - Generic message arrays (
messages,history,conversations,dialog,turns) - Pair fields (
question-answer,prompt-response,input-output)
If format detection fails, stop and ask the user for a sample snippet, then extend parsing rules.
Run Script
python3 scripts/convert_conversations.py \
--input /path/to/<user-provided>.json \
--output-dir /path/to/output_md \
--clean
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.
- 11d ago First seen · 104 lines · 28 tokens per session scan A d11b9d57ddfc
conversation-json-to-md is a skill published in the GitHub repository YangsonHung/awesome-agent-skills (18 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 708 once invoked, about $0.0001 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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