一键导入
memory-slack-ingest
Ingest Slack DMs and important channel messages into the memory knowledge base
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Ingest Slack DMs and important channel messages into the memory knowledge base
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | memory-slack-ingest |
| description | Ingest Slack DMs and important channel messages into the memory knowledge base |
| user_invocable | true |
Pull recent Slack direct messages and important threads, extract decisions and context, append to daily log.
Read state from /Users/jesseanglen/Documents/RandomStuff/memory-kb/state/slack-state.json.
If it doesn't exist, this is the first run — set last_checked to 3 days ago (Unix timestamp).
Jesse's Slack user ID: U01TKLJK04B
Use slack_search_public_and_private to find recent DMs:
query: "to:me"
channel_types: "im,mpim"
sort: "timestamp"
sort_dir: "desc"
limit: 20
If last_checked exists, use after parameter with the Unix timestamp.
Also search for messages from Jesse in DMs:
query: "from:<@U01TKLJK04B>"
channel_types: "im,mpim"
For each DM found, check if it's substantive (not just "thanks" / "ok" / emoji reactions).
For substantive messages, use slack_read_thread with the channel_id and message_ts to get the full conversation context.
What's substantive:
Skip:
Check if the DM sender appears in /Users/jesseanglen/Documents/RandomStuff/memory-kb/state/calendar-contacts.json.
If they do, note the related_event for context linking.
For each substantive DM thread, append to /Users/jesseanglen/Documents/RandomStuff/memory-kb/daily/YYYY-MM-DD.md:
## Slack DM from [Name] @ HH:MM PT
**source:** slack
**from:** [Real Name] (Slack: @username)
**channel_type:** DM | Group DM
**related_event:** [if sender is in calendar contacts, reference their last meeting]
### Key Content
- [Summary of the conversation thread]
- [Decisions made or information shared]
- [Action items or requests]
### Action Items
- [ ] [Any follow-ups identified]
Create daily log with header if it doesn't exist.
Write to /Users/jesseanglen/Documents/RandomStuff/memory-kb/state/slack-state.json:
{
"last_checked": "Unix timestamp",
"total_runs": N,
"last_run": {
"timestamp": "ISO",
"dms_found": N,
"dms_ingested": N,
"threads_read": N,
"status": "success"
},
"processed_message_ts": ["ts1", "ts2"]
}
Keep last 200 processed message timestamps for dedup.
"Slack ingest complete. Found X DMs, ingested Y substantive threads."
slack_search_public_and_private — search DMs and channelsslack_read_channel — read recent messages from a DM (use user_id as channel_id)slack_read_thread — read full thread repliesslack_search_users — look up user details by nameslack_read_user_profile — get user profile infoIngest Bubbles AI meeting summaries from Gmail into the memory knowledge base
Pull Google Calendar events via MCP tools and extract attendees into the memory-kb contact registry
Manually compile daily logs into knowledge articles and run structural lint
Ingest emails from calendar contacts using Gmail MCP tools — calendar-gated to prevent spam/noise
Ingest recently modified Google Docs into the memory knowledge base with email correlation
Query the personal knowledge base — ask questions about past decisions, meetings, and context