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 dashhuang/openclaw-chat-history-import --skill conversation-historygit clone --depth 1 https://github.com/dashhuang/openclaw-chat-history-importWrote 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/dashhuang/openclaw-chat-history-import/conversation-history)<a href="https://agentmods.dev/skills/dashhuang/openclaw-chat-history-import/conversation-history"><img src="https://agentmods.dev/badge/skills/dashhuang/openclaw-chat-history-import/conversation-history/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/dashhuang/openclaw-chat-history-import/conversation-history"><img src="https://agentmods.dev/badge/skills/dashhuang/openclaw-chat-history-import/conversation-history.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 | $0.00070 | $0.00780 |
| Opus 5 | $0.00035 | $0.00390 |
| Sonnet 5 | $0.00014 | $0.00156 |
| Haiku 4.5 | $0.00007 | $0.00078 |
Grade A, and why
conversation-history 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conversation History
Use this skill for historical recall across many kinds of chat history, not just live messaging channels.
Scope
This skill works by searching the local raw archive tree:
logs/message-archive-raw/
That means it can search any chat history that has already been normalized into that archive format.
Typical sources include:
- Telegram
- BlueBubbles / iMessage relay
- Feishu
- ChatGPT exports imported through
chat-history-import - Claude exports imported through
chat-history-import - other archive-compatible chat logs
The conversation-archive plugin code also has explicit mappings ready for WhatsApp, Discord, Signal, Webchat, Slack, and Line if those channels are enabled later.
So this skill should be thought of as a general archive search skill, not just a Telegram / Feishu recall helper.
If the archive data exists in logs/message-archive-raw/, this skill can search it.
Workflow
- Start with
memory_searchfor topic, person, or decision recall. - If the user wants exact wording, exact links, chronology, or channel-specific confirmation, run:
python3 skills/conversation-history/scripts/search_archive.py --query "keyword" --limit 8
- Add filters when useful:
python3 skills/conversation-history/scripts/search_archive.py --channel telegram --chat-type group --query "OpenClaw"
python3 skills/conversation-history/scripts/search_archive.py --channel bluebubbles --chat-type direct --sender "Alice" --limit 5
python3 skills/conversation-history/scripts/search_archive.py --channel feishu --from-date 2026-03-01 --to-date 2026-03-14 --query "Confluence"
python3 skills/conversation-history/scripts/search_archive.py --channel chatgpt --query "memory export"
python3 skills/conversation-history/scripts/search_archive.py --channel claude --query "project plan"
python3 skills/conversation-history/scripts/search_archive.py --query "shareholder letter" --limit 5
Use channel filters when the source is known. If the user only cares about content recall and not the original source, broad keyword search is often enough.
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 · 81 lines · 70 tokens per session scan A 73647cf44251
conversation-history is a skill published in the GitHub repository dashhuang/openclaw-chat-history-import (142 stars, last pushed 5mo ago), licensed MIT. It adds 70 tokens to every session and 780 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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