Topoteretes

Use when configuring the Cognee connection, checking whether Cognee is ready or connected, or diagnosing a local or cloud Cognee instance from Antigravity.

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A multi-day digest of the user's own coding-agent sessions — sessions per day and project, most-edited files, and every lesson Cognee distilled into the knowledge graph in that window. Use only when the user explicitly asks for a weekly digest, a retro, a recap or report of their recent sessions, or asks for the `cognee-digest` skill by name. Not for questions about code or the current task.

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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.

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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.

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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.

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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.

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Use when reviewing, fixing, or verifying a pull request. Focus on correctness regressions, missing tests, permission mistakes, unsafe behavior, and minimal fixes.

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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.

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