55 skills (repositories by topoteretes) · sorted by popularity
Draft a reply to the newest Gmail inbox message using Granola meeting notes and past emails stored in cognee. Incorporates prior discussions, commitments, and writing style, then displays the draft without sending it.
Turn the latest Granola call into action items with owners, teams, due dates, and matching existing Linear issues. It uses cognee memory of calls, issues, and Gmail, then prints the results or posts them to configured Slack.
Ask questions about your journal, Obsidian vault, or other text notes, and continue conversations that remember earlier chats. The companion uses cognee memory with local databases, reads your notes without changing them, and saves conversations for later reference.
Connect a company SQL database, support ticket exports, and documents in cognee, linking shared people, teams, and projects so questions about ownership, decisions, and ongoing work can draw on several sources together.
Import text, files, URLs, repositories, and database content into cognee memory. This skill explains input handling, storage organization, extraction options, and cost estimates, while helping diagnose unsupported arguments and document update errors.
Operate cognee from the terminal to store, retrieve, update, and remove information. Covers dataset and configuration management, ingestion cost estimates, session history access, and commands for inspecting or applying database migrations.
Set up users, organizations, roles, and dataset sharing in cognee. The skill explains SDK and HTTP authentication, helps investigate permission errors or missing datasets, and clarifies how access settings separate each user’s stored data.
Run cognee in Docker, starting with a prebuilt image for local document ingestion and questions. It also covers Docker Compose profiles for adding the UI, MCP server, Postgres, and Neo4j, plus persistent data storage.
Set up cognee and run a first Python example that stores information and retrieves it with a question. Covers virtual environments, API key configuration, optional packages, and basic troubleshooting.
Connect cognee to model providers, databases, storage services, and development tools. Guides configuration of language models and embeddings, the numerical representations used for search, including the separate settings each requires.
Find and remove stored content from cognee using its SDK, HTTP API, or CLI. Inspect documents before deletion, choose document or dataset removal, or keep raw files while clearing derived graph relationships and search vectors.
Store conversations, agent activity, and feedback in cognee sessions, then carry them into long-term memory. This skill explains improve(), its processing stages, result statuses, and settings for diagnosing skipped work or controlling automatic runs.
Query documents and conversations stored in cognee to retrieve answers, supporting passages, or context for an AI model. This skill guides search method selection, source filtering, result interpretation, and troubleshooting empty or unexpected results.
Manage cognee database migrations, from checking migration status and recovering blocked writes to creating schema or data updates. It also guides dataset backups, restores, and transfers using cognee’s portable COGX archive format.
Build custom cognee processing by chaining Python tasks, defining data types, and saving results to graph and vector databases. Use it to enrich existing data, inspect run status, and troubleshoot how tasks pass data.
Run the cognee API server and optional interface on your own machine, check server health, connect SDK or HTTP clients, and configure authentication for personal development or use by multiple users.
Connect cognee to additional databases and data sources through community packages. The skill covers installing and registering adapters, importing data through connectors, configuring monitoring, and developing extension packages with examples and tests.
Tune cognee ingestion speed, query response time, and LLM costs by adjusting concurrency, text chunk sizes, request limits, and model choices. Estimate ingestion costs before processing and assess options for background work and deployment scaling.
Define custom entities and relationships in cognee, a memory system for AI applications. This skill guides model design, identity matching, searchable fields, and troubleshooting when entities are duplicated or relationships are missing.
Search Cognee memory. Session memory is automatically searched on every prompt via hooks. Use this skill explicitly for permanent knowledge graph search, filtered category search, or when you need more results than the automatic lookup provides.
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Evaluate Cognee itself from local telemetry: recall hit rate, latency, saves, injected context, tokens saved, a scorecard and grade, before vs after an update, and why a memory was or wasn't injected last turn.
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Explain a repository's architecture (modules, routes, storage, services), find risky hotspots, draw a Mermaid diagram of the code graph, or review how far a change reaches, from Cognee's code graph.
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Write a concise handoff note for the current work (goal, decisions, open items, next steps, branch and PRs) and save it in Cognee so a later session can pick up where the work stopped.
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Explain what the Cognee plugin captures, recalls, stores and sends, where its data and logs live, and how to inspect or turn off each behavior; check its local or cloud connection and settings.
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