一键导入
memory-test
Run E2E memory pipeline test — embed text, store in Qdrant, search and retrieve. Use to validate the memory system is working.
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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Run E2E memory pipeline test — embed text, store in Qdrant, search and retrieve. Use to validate the memory system is working.
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
Run the full integration test suite
Resume from last checkpoint — show progress, cluster state, next actions
Deploy Kaizen components with safety checks and validation
Development workflow for Kaizen - branching, commits, testing
Launch autonomous overnight build session with Ralph Wiggum
Emergency rollback for Kaizen deployments
| name | memory-test |
| description | Run E2E memory pipeline test — embed text, store in Qdrant, search and retrieve. Use to validate the memory system is working. |
| allowed-tools | Bash |
Run the full embed → store → search pipeline:
Start port-forward (if not already running):
kubectl port-forward svc/qdrant -n vector 6333:6333 &
sleep 2
Generate embedding:
curl -s http://10.10.10.10:30001/v1/embeddings \
-H "Content-Type: application/json" \
-d '{"model":"default","input":"Kaizen memory pipeline test at '"$(date -Iseconds)"'"}'
Verify: 4096 dimensions returned.
Store in Qdrant:
Use the embedding from step 2 to upsert a point into the episodic collection with a random UUID and timestamp payload.
Search:
Generate a new embedding for a related query and search the episodic collection. Verify score > 0.5.
Report:
| Step | Status | Details |
|---|---|---|
| Embedding | ? | dims, latency |
| Store | ? | collection, point ID |
| Search | ? | score, matches |
Cleanup port-forward:
kill %1 2>/dev/null