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。
topoteretes/cognee3.2万2026年10月13日 更新
無料GitHub で公開
company-brain-follow-up-agent
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.
含まれるファイル（1）
- SKILL.md3.0 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Company brain: agent for follow-up
Runs the follow-up agent cookbook in examples/cookbooks/company_brain/follow_up_agent/.
It remembers your Granola calls, Linear issues and Gmail inbox in the cognee dataset
follow_up_agent, then works out the next steps of your latest call and posts them to
Slack, or prints them. Setup, the scripts and what each one does are in the cookbook's
README.md.
Run every command from the repo root.
Steps
With none of Granola, Linear and Gmail set up, the commands below run on sample calls,
issues and email (the [setup] line says so), follow up a fictional call and never post to
Slack; only LLM_API_KEY is needed. Tell the user the steps come from sample data. Add
--sample to use the sample even when their accounts are set up.
- Run
uv run python examples/cookbooks/company_brain/follow_up_agent/follow_up_agent.py --check.- Exit 0: go to step 2.
[setup] SKIPPED:lines name optional sources that won't be used; mention them to the user, but they don't block the run. - Exit 2: each
[setup] MISSING:line names one fix. Don't create credentials yourself. Tell the user exactly which line to fix, using the README's "What it needs" table, and stop.
- Exit 0: go to step 2.
- Run
uv run python examples/cookbooks/company_brain/follow_up_agent/follow_up_agent.py. Add--days Nif the user named a time range, and--no-linear/--no-emailif they don't want a source used. - The steps are everything after the
[follow_up] Posted to Slack:or[follow_up] Stepsline. Give them to the user, say which call they come from (the[follow_up] Call:line), which sources went in (the[ingest_*]lines), and whether they were posted. - If a script fails,
follow_up_agent.pyexits 1 with a line naming what went wrong. Run that script fromexamples/cookbooks/company_brain/follow_up_agent/scripts/on its own to look closer.
Rules
- Gmail access is read-only.
- With Slack set up, a run posts to the user's real channel, and every run reads the user's real calls, issues and mailbox and uses LLM credits, so run it only when the user asked for it.
- Don't print the contents of
credentials.json,token.jsonor.env. - A sample run forgets the cookbook's dataset
follow_up_agentbefore it ingests (the[clear]line). On the user's own data, pass--clearonly when they asked to start over: it forgets everything the dataset holds. - Don't pass
--uiunless the user asked to browse the graph: it keeps running until Ctrl+C.
Clean up
uv run cognee-cli forget --dataset follow_up_agent
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
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。
topoteretes/cognee3.2万2026年10月13日 更新
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。
topoteretes/cognee3.2万2026年10月13日 更新
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。
topoteretes/cognee3.2万2026年10月13日 更新
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。
topoteretes/cognee3.2万2026年10月13日 更新
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。
topoteretes/cognee3.2万2026年10月13日 更新