Feishu Group Memory

Architecture

Scripts handle data only — no LLM calls inside scripts: - onboarding.py — read/write industry knowledge pack config - listener.py — fetch raw messages from Feishu; save analyzed records - query.py — keyword search over stored records - billing.py — SkillPay charge/balance/payment-link

All AI analysis is done by you (the OpenClaw model): deciding what to record, extracting structured fields, generating advice, writing summaries.

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Quick Reference

Operation	Script	Billed
Check industry config	onboarding.py check	Free
Load built-in industry pack	onboarding.py setup --industry	Free
Save custom industry pack	onboarding.py save --content	Free
Find group by name	listener.py find_chat --name	Free
Fetch raw messages	listener.py fetch_raw	Free
Save analyzed records	listener.py save_records	Free
Search records	query.py search	Free
List records by period	query.py list_records	Free
Fetch + analyze messages	(fetch_raw → you analyze → save_records)	0.005 USDT
Get AI advice	(query → you advise)	0.003 USDT
Generate summary report	(list_records → you summarize)	0.005 USDT

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First Use: Onboarding

At the start of every session, check whether an industry pack is configured:

python3 {baseDir}/scripts/onboarding.py check --workspace ~/.openclaw/workspace

• {"configured": true, "context": "..."} → load the context field and proceed
• {"configured": false} → run onboarding before anything else

Onboarding conversation

Ask the user:

"Before we start, I'd like to understand what your group is mainly used for so I can record and analyze the right things.

Choose one, or describe it in your own words: 1. 📈 Sales tracking (leads, quotes, deals) 2. 🎧 Customer support (tickets, issues, complaints) 3. ⚖️ Legal matters (contracts, risks, cases) 4. 📋 Project management (tasks, milestones, blockers) 5. ✍️ Describe my own use case"

Saving the config

Built-in industry (options 1–4):

python3 {baseDir}/scripts/onboarding.py setup 
  --industry sales 
  --workspace ~/.openclaw/workspace

Valid slugs: sales / customer-service / legal / project

Custom description (option 5):

Using the user's description and the template at {baseDir}/templates/context-template.md, generate the knowledge pack yourself, then save it:

python3 {baseDir}/scripts/onboarding.py save 
  --content "YOUR GENERATED CONTENT" 
  --workspace ~/.openclaw/workspace

Confirm with the user: "Got it! I'll use this context going forward. Which group would you like me to start recording?"

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Feature: Record Group Messages

Trigger: "record X group", "fetch messages from X", "capture what's been discussed in X"

Step 1 — Find the group

python3 {baseDir}/scripts/listener.py find_chat --name "KEYWORD"

If multiple results, show them and ask the user to pick one.

Step 2 — Fetch raw messages

python3 {baseDir}/scripts/listener.py fetch_raw 
  --chat_id CHAT_ID 
  --limit 100 
  --workspace ~/.openclaw/workspace

Returns an array of {msg_id, time, sender, text} objects.

Step 3 — You analyze

Using the loaded industry knowledge pack (from onboarding check), go through each message and decide: - Is it worth recording? - What category does it belong to? - Who or what is the key entity (person, company, project)? - What structured fields can be extracted? - What is the urgency (high / medium / low)?

Step 4 — Save the records

python3 {baseDir}/scripts/listener.py save_records 
  --chat_id CHAT_ID 
  --workspace ~/.openclaw/workspace 
  --records '[{"msg_id":"...","time":"...","sender":"...","raw_text":"...","category":"...","key_entity":"...","summary":"...","fields":{...},"urgency":"high"}]'

Step 5 — Report to user

Summarize what was found, e.g.:

"Analyzed 100 messages. Saved 12 items: - 3 customer intent signals (Li, Wang, Chen) - 5 follow-up actions - 4 pricing discussions

2 high-urgency items — want me to walk through them?"

Billing

python3 {baseDir}/scripts/billing.py charge 
  --user_id USER_ID --amount 0.005 --label "message analysis"

If payment_required is returned, show the top-up link and stop.

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Feature: Query Records

Trigger: "how is Wang doing", "what happened with Acme last week", "show me recent follow-ups"

python3 {baseDir}/scripts/query.py search 
  --query "KEYWORD" 
  --workspace ~/.openclaw/workspace

Returns matching records as raw JSON. You turn them into a natural-language answer, e.g.:

"Here's what I have on Wang (Wang Zong): - Jan 15: Said he can sign next week (high priority) - Jan 12: Asked about discount options, still considering

Last contact was 3 days ago — worth reaching out today."

No charge for queries.

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Feature: AI Advice

Trigger: "how should I follow up with X", "give me some advice", "help me think through this"

First, search for relevant records:

python3 {baseDir}/scripts/query.py search 
  --query "KEYWORD" 
  --workspace ~/.openclaw/workspace

Then reload the industry pack if needed:

python3 {baseDir}/scripts/onboarding.py check --workspace ~/.openclaw/workspace

Using the "Advice Templates" section of the knowledge pack and the retrieved records, give the user concrete, actionable advice directly.

python3 {baseDir}/scripts/billing.py charge 
  --user_id USER_ID --amount 0.003 --label "AI advice"

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Feature: Summary Report

Trigger: "summarize today", "weekly report", "what happened this week"

python3 {baseDir}/scripts/query.py list_records 
  --period today|week|all 
  --workspace ~/.openclaw/workspace

You write the summary. Example structure:

Weekly Summary (Jan 13–19)

28 items recorded across 7 customers.

Action required (3) - Li Zong: ready to sign — prepare draft contract - Wang Zong: price sticking point — request special approval

By category - Customer intent: 12 | Follow-ups: 8 | Pricing: 5 | Other: 3

Suggestion: 2 customers haven't been contacted in 5+ days.

python3 {baseDir}/scripts/billing.py charge 
  --user_id USER_ID --amount 0.005 --label "summary report"

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Error Handling

Situation	Response
No industry pack configured	Run onboarding first
Group not found	"I couldn't find a group called 'X'. Could you give me the full name?"
No records yet	"Nothing recorded yet. Want me to fetch messages from that group now?"
payment_required	Show the top-up link from message field, stop, wait for user
Missing Feishu credentials	Ask user to configure channels.feishu.accounts in openclaw.json