Agent Skills › topoteretes/cognee › company-brain-company-qa

company-brain-company-qa

GitHub

构建公司知识库,整合SQL数据库、工单导出和文档,利用cognee生成本地知识图谱以回答跨源问题。

.agents/skills/company-brain-company-qa/SKILL.md topoteretes/cognee

Trigger Scenarios

需要连接公司的数据库、工单和文档 询问谁拥有、决定或处理某事

Install

npx skills add topoteretes/cognee --skill company-brain-company-qa -g -y
More Options

Non-standard path

npx skills add https://github.com/topoteretes/cognee/tree/main/.agents/skills/company-brain-company-qa -g -y

Use without installing

npx skills use topoteretes/cognee@company-brain-company-qa

指定 Agent (Claude Code)

npx skills add topoteretes/cognee --skill company-brain-company-qa -a claude-code -g -y

安装 repo 全部 skill

npx skills add topoteretes/cognee --all -g -y

预览 repo 内 skill

npx skills add topoteretes/cognee --list

SKILL.md

Frontmatter
{
    "name": "company-brain-company-qa",
    "description": "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."
}

Company brain: company Q&A

Runs the company brain cookbook in examples/cookbooks/company_brain/company_qa/. It remembers a SQL database, a ticket export and a docs folder in the cognee dataset company_qa, extracts them with one graph model so the same person, team or project becomes one node, then answers a question across them. Setup, the scripts and what each one does are in the cookbook's README.md.

Run every command from the repo root.

Steps

  1. Work out the sources. Ask the user for the ones they want: a database URL (and tables), one or more ticket export files (JSON or CSV), a docs folder. If they have none, or want to see it work first, pass no sources: the run then uses the sample company (the [setup] line says so). Tell the user the answer comes from sample data.
  2. Run uv run python examples/cookbooks/company_brain/company_qa/company_qa.py --check with the sources (--database URL [--tables a,b] --tickets FILE [FILE ...] --docs FOLDER), or none for the sample.
    • Exit 0: go to step 3.
    • Exit 2: each [setup] MISSING: line names one fix. Don't create credentials yourself. Tell the user which line to fix, using the README's "What it needs" table, and stop.
  3. Run the same command without --check, adding the user's question as --ask "...". On the sample with no --ask, it asks a question that needs all three sample sources.
  4. The answer is everything after [ask] A:. Give it to the user. The [ingest] lines say which sources went in.
  5. Later questions don't need the sources again: uv run python examples/cookbooks/company_brain/company_qa/scripts/ask.py "...".
  6. If a script fails, company_qa.py exits 1 with a line naming what went wrong. Run that script from examples/cookbooks/company_brain/company_qa/scripts/ on its own to look closer.

Rules

  • The sources are the user's company data. Don't quote them beyond what answers the question, and don't print .env or a database URL's password.
  • Every run uses LLM credits, so ingest only when the user asked for it.
  • A sample run forgets the cookbook's dataset company_qa before it ingests (the [clear] line). On the user's own data, pass --clear only when they asked to start over: it forgets everything the dataset holds.
  • Don't pass --ui unless the user asked to browse the graph: it keeps running until Ctrl+C.

Clean up

uv run cognee-cli forget --dataset company_qa

Version History

  • 37f788b Current 2026-10-19 05:49

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2026-10-19 05:49

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