Use at a cognee hackathon. Watches the participant's experience with cognee throughout the session — errors, slowness, confusion, workarounds, and signs of frustration in how they work with you — and keeps one private feedback file they send to the cognee team at the end.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
topoteretes/cognee-hackathons☆ 112026년 10월 18일 업데이트
Use at the Mem Off hackathon. Keeps a running, evidence-backed report on how the participant's memory system performed for their coding agent during the day — what the harness measured, what cognee-report's scorecard says, what was recalled and whether it helped — in ./memoff-report.md and ./memoff-report.json. The report is submitted together with the action results; it never contains quotes, keys, data or names.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
topoteretes/cognee-hackathons☆ 112026년 10월 18일 업데이트
Build spend analytics and dashboards from Qdrant vector data. Covers bulk scroll extraction, aggregation patterns, vendor grouping, and Chart.js visualization. Use when building analytics features, aggregating procurement data, or creating dashboards.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
topoteretes/cognee-hackathons☆ 112026년 10월 18일 업데이트
Detect anomalies in procurement data using Qdrant vector operations. Covers centroid-based outlier detection, near-duplicate finding via batch recommend, amount z-score analysis, and vendor variance scoring. Use when building anomaly detection, fraud detection, or data quality features.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
topoteretes/cognee-hackathons☆ 112026년 10월 18일 업데이트
Semantic search over Qdrant Cloud collections using the Python client. Covers vector search, filtered search, prefetch+RRF fusion, group API, recommend API, discovery API, batch queries, scroll, and payload indexing. Use when building search features, adding new query types, or working with qdrant-client.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
topoteretes/cognee-hackathons☆ 112026년 10월 18일 업데이트