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Chat with a companion that knows your notes folder (a journal, an Obsidian vault, any .md or .txt files) and every earlier chat, using cognee memory with local databases. Use when someone wants to ask questions about their own notes, or to talk with a companion that remembers past conversations. Runs locally; reads the notes folder, writes only to cognee's memory.

日本語の概要は準備中です。原文の説明を表示しています。

Turn your latest Granola call into next steps (owner, team, due date, and the Linear issue that already tracks each one) and post them to Slack, using cognee memory of your calls, Linear issues and Gmail inbox. Use when someone asks for the next steps or action items of their latest call. Runs locally; reads Gmail read-only; posts to Slack only when Slack is set up.

日本語の概要は準備中です。原文の説明を表示しています。

Draft a reply to your newest Gmail email that knows what you discussed in your Granola meetings, what you promised the sender, and how you write, using cognee memory. Use when someone asks to answer or reply to their latest email in their own tone. Runs locally; reads Gmail read-only; the draft is printed, never sent.

日本語の概要は準備中です。原文の説明を表示しています。

Build one company memory from a SQL database, a support ticket export and a folder of documents, linked into one graph by cognee, then answer questions that need several of those sources together. Use when someone wants to connect their company's database, tickets and docs, or asks who owns, decided or is handling something across them. Runs locally; reads the sources, writes only to cognee's memory.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to run the cognee API server (and optional UI) on their own machine — starting it, checking it's healthy, connecting the SDK or other clients to it, and choosing the right auth posture.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building your own cognee processing — writing custom tasks, chaining them into a pipeline with run_custom_pipeline or the lightweight run_pipeline (from cognee.pipelines import run_pipeline), storing custom DataPoints with add_data_points, running custom extraction/enrichment over the existing graph with memify, checking pipeline run status, or debugging how data flows between tasks (batch_size, data_per_batch, ctx, Drop, enriches).

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.

日本語の概要は準備中です。原文の説明を表示しています。

Use when putting data into cognee memory with remember() — choosing inputs (text, files, folders, URLs, repos, databases), datasets and node_sets, loaders, ontologies, the graph extractor (LLM or GLiNER), chunking, dry-run cost estimates, or when remember() raises on a keyword argument.

日本語の概要は準備中です。原文の説明を表示しています。

Use when cognee is slow, expensive, or hitting rate limits — speeding up or throttling ingestion (remember/cognify batching, chunk size, LLM and embedding rate limits, per-stage models), cutting read latency, estimating cost before ingesting, running work in the background, or planning how to scale a deployment.

日本語の概要は準備中です。原文の説明を表示しています。

Use when defining the shape of cognee's knowledge graph with graph_model= — writing DataPoint node classes, choosing identity and index fields so nodes merge and are searchable, declaring typed Edge fields and FromIdentity references, building a model from a JSON schema, or debugging duplicated nodes, missing edges, or InvalidReferenceTypeError.

日本語の概要は準備中です。原文の説明を表示しています。

Use when querying cognee memory with recall() (or search()) — picking a search type, understanding auto-routing, scoping to datasets, node sets or sessions, getting context or citations instead of an answer, reading the results, or debugging empty or unexpected results.

日本語の概要は準備中です。原文の説明を表示しています。

Use when removing data from cognee memory with forget() in the SDK, HTTP API, or CLI — finding which dataset and document hold the content to delete (listing datasets and data items, reading raw content), choosing between deleting one document, a whole dataset, or only the graph/vector memory, and doing it safely.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to connect cognee to external services — switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing databases (Postgres, PGVector, Neo4j, Neptune, Turso), S3 storage, or the MCP server for IDE integration.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to install cognee and run their first remember → recall flow with the Python SDK — fresh setup, virtual env, extras selection, or a minimal working example.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with cognee's session memory or improve() — storing conversation turns, agent traces and feedback with session_id, bridging sessions into the permanent graph, reading an ImproveResult, understanding why an improve stage was skipped, already_completed or lock_held, or tuning the IMPROVE_* settings.

日本語の概要は準備中です。原文の説明を表示しています。

Use when dealing with cognee database migrations — understanding when they run automatically, checking or repairing migration state with cognee-cli upgrade/downgrade/stamp/current, a write blocked by a failed migration, authoring a new Alembic (relational schema) revision or a graph/vector data migration, or moving data between systems (relational DB import, memory export/import).

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to run cognee with Docker or docker compose — trying it out from the prebuilt image, starting the API server in a container, or bringing up the full stack (UI, MCP, Postgres, Neo4j) with compose profiles.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with cognee's users, permissions, and multi-tenancy — creating users, tenants and roles, sharing datasets (read/write/delete/share grants), acting as a specific user in the SDK or authenticating over HTTP (login, API keys), turning access control on or off, debugging PermissionDeniedError or missing datasets, or understanding where permissions are enforced and how datasets are isolated.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user needs something that ships outside cognee core — community database adapters (Qdrant, Milvus, Weaviate, Redis, Pinecone, FalkorDB, Memgraph, DuckDB, NetworkX, …), data-source connectors (Slack, Gmail, Notion, Confluence, Google Drive), custom tasks/pipelines/retrievers (Exa, ScrapeGraph, codify), Keywords AI observability — or wants to contribute a package to the cognee-community repo.

日本語の概要は準備中です。原文の説明を表示しています。

Index a code repository into Cognee's code graph and query it deterministically (callers, impact analysis, paths, endpoints). Use for structural code questions, "index this repo", and checking what a re-index changed.

日本語の概要は準備中です。原文の説明を表示しています。

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 invokes /cognee-digest. Not for questions about code or the current task.

日本語の概要は準備中です。原文の説明を表示しています。

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

日本語の概要は準備中です。原文の説明を表示しています。

Use only when the user explicitly asks to launch or inspect the LOCAL Cognee UI (the cognee-cli dev UI). For "is Cognee running/connected" or any configuration question, use the setup skill instead. Does not apply in cloud mode.

日本語の概要は準備中です。原文の説明を表示しています。

Forget data stored in Cognee memory. Use when the user asks to forget, delete, or remove something from memory (e.g. "forget what we talked about tennis", "delete that from memory"). Finds the documents in the current dataset whose raw content matches what the user wants forgotten and deletes them.

日本語の概要は準備中です。原文の説明を表示しています。