Provide a team ID, bot ID, and question. AI can search DocsBot sources, read the matching documents, and prepare an answer with references.
Copy a prompt into your agent with the oo Skill installed. Add your page links and source notes before running it.
Search source chunks and retrieve relevant reconstructed documents to prepare a referenced answer.
/oo DocsBot AI: Search DocsBot team [team ID], bot [bot ID] for [question]. Fetch the relevant documents using result file IDs, then answer with source references and identify any gaps in the retrieved material.
Set up oo CLI and the oo Skill in your agent.
Install OOMOL →Connect with a DocsBot user API key.
Connect DocsBot AI →Use /oo with the pages to read, the changes to make, and where to save the result.
Connection Guide →Choose Your Agent
DocsBot trained sources are searchable as text chunks. Reconstructed document retrieval adds surrounding context for source-based research and answers.
Search trained source chunks with optional filters and retrieve reconstructed document text by result file ID.
List and inspect accessible teams and bots, including status and source metadata.
List DocsBot teams visible to the API key user.
Leina 
Wanta 
docsbot_ai.list_teams Get a DocsBot team by ID.
docsbot_ai.get_team List DocsBot bots in a team.
docsbot_ai.list_bots Get a DocsBot bot by team and bot ID.
docsbot_ai.get_bot Search a DocsBot bot's trained source chunks by natural-language query.
docsbot_ai.semantic_search Fetch the full reconstructed document text for a DocsBot search result file ID.
docsbot_ai.fetch_document No matching tools.
Yes. Keep the search result’s source information alongside the claims supported by its text.
Yes. Use a search result’s file ID to retrieve the full reconstructed document text.
These operations read teams, bots, and existing trained sources; they do not upload or train new sources.
Manage which optional storage OOMOL can use. You can change these choices from the footer at any time.