「cognee」の検索結果

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 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 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 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 the user says 'cognee', asks about knowledge graph or graph memory, wants to switch memory backends, or needs a status check, dataset init, or graph view. Covers Cognee endpoints plus the Brain fallback.

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 says 'cognee store', 'push to cognee', 'save to graph', 'remember this' or 'log this decision', or when session decisions must be stored. Writes entities, decisions and events over POST /api/v1/remember.

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 says 'cognee recall', 'search memory', 'what do we know about', 'find related', or 'graph search'. Runs semantic, graph, and lexical search across the Cognee knowledge graph and injects results as agent context.

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 dated chronology of one topic across the user's recorded coding-agent sessions — the lessons the graph learned about it and the prompts that named it, oldest first. Use only when the user explicitly asks for the history or timeline of a topic across their sessions ("how did X evolve", "when did we first discuss X") or invokes /cognee-timeline. 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。

Store data permanently in the Cognee knowledge graph. Accepts a data category (user, project, or agent) to tag the data with the correct node_set for filtered retrieval.

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。

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.

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。

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。

AI knowledge engine - a memory system in 6 lines of code. remember/recall/forget/improve loop, vector + graph search, OpenClaw plugin supported.

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 dated chronology of one topic across the user's recorded coding-agent sessions — the lessons the graph learned about it and the prompts that named it, oldest first. Use only when the user explicitly asks for the history or timeline of a topic across their sessions ("how did X evolve", "when did we first discuss X") or asks for the `cognee-timeline` skill by name. 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。

Sync session cache entries into the permanent Cognee knowledge graph. Run this to make session memory searchable, or it runs automatically at session end.

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。

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。

Routes Cognee AI memory platform tasks across SDK memory APIs, graph/RAG retrieval, configuration, custom pipelines, session memory, CLI, API, MCP, and deployment workflows.

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 indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) 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 when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Antigravity.

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 Codex should remember, recall, search, improve, or forget information using Cognee.

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 Antigravity should remember, recall, search, improve, or forget information using Cognee.

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 Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

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 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.

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。