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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 standup or status update built from the coding-agent sessions Cognee recorded — prompts, tool calls, edited files, what was left open — per project. Use only when the user explicitly asks for a standup, a status update, a catch-up on their own recent sessions ("what did I work on yesterday / this week"), or invokes /cognee-standup. Not for questions about code, files 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。

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。

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.

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。

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。

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。

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。

Switch this session to another Cognee dataset. Lists the datasets you can write to, lets you pick one, syncs the current session into its dataset, then starts a fresh Cognee session bound to the chosen dataset. All later saves and recalls target the new dataset and the status line shows it.

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。

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。

Use when an agent must stand up the OpenClaw↔Cognee integration with FalkorDB as the vector + graph store. This skill is SELF-CONTAINED — it tells you to generate every file (Dockerfile, sitecustomize.py, docker-compose.yaml) from the exact contents below, build a custom Cognee image that loads the FalkorDB adapter, run Cognee + FalkorDB together, self-verify the adapter registered, and point the OpenClaw cognee plugin at it (including per-agent graphs). No other files in this directory are required.

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。

A standup or status update built from the coding-agent sessions Cognee recorded — prompts, tool calls, edited files, what was left open — per project. Use only when the user explicitly asks for a standup, a status update, a catch-up on their own recent sessions ("what did I work on yesterday / this week"), or asks for the `cognee-standup` skill by name. Not for questions about code, files 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 the user wants to switch this Codex session to another Cognee dataset, see which datasets are available, or move memory capture to a different dataset. Syncs the current session first, then starts a fresh Cognee session bound to the chosen dataset.

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。

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。

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。

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

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。

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.

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 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.

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。

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.

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。