create_code
ChatGPTCreate a new qualitative code in the project. Codes are used to categorize/tag text segments during analysis.
Overview
SuperQDA connects your qualitative research workspace to ChatGPT. Access your research projects, documents, codes, and analyses directly in conversation. What you can do: - Browse and read all your uploaded documents (PDFs, Word files, transcripts) - Perform semantic search across your research data using perform_semantic_search - Create and apply qualitative codes to text segments using create_code and create_coded_segment - Write analytical memos and save structured analyses - Search for keywords across all project documents with perform_text_search SuperQDA is a qualitative data analysis (QDA) platform used by researchers, academics, and students for thematic analysis, grounded theory, and other qualitative methodologies. This integration lets you leverage ChatGPT's reasoning capabilities directly on your research data without leaving the conversation. All data access is secured with OAuth 2.0 + PKCE. Your credentials are never shared with ChatGPT.
Tools
create_coded_segment
ChatGPTTag a text segment in a document with a code. This is the core coding action in qualitative data analysis.
create_memo
ChatGPTCreate an analytical memo. Memos capture researcher reflections, theoretical notes, and methodological decisions.
delete_code
ChatGPTPermanently delete a qualitative code. All text segments coded with it (and their segment memos), its code memos and all code relations involving it are deleted. By default its child codes are moved up to its parent (childStrategy "reparent"); "delete_subtree" also deletes all descendant codes and their segments. Use dryRun to preview the impact and confirm with the user first.
delete_coded_segment
ChatGPTRemove a code from a text segment (delete the coded segment and its segment memos). The document text is not changed. Segment IDs come from get_coded_segments.
get_coded_segments
ChatGPTGet text segments that have been coded (tagged) with a specific code. Shows exactly which text was marked with which code.
get_dataset_info
ChatGPTDescribe a quantitative dataset before analysing it: variables (id, name, label, kind, measure, role, value labels, missing codes, reverse-scored flag, which analysis inputs each can be used for) with a short summary (n, missing, mean/SD/min/max or category counts), scales with subscales, and the open-ended documents and codes linked to it (for run_mixed_analysis). Never returns raw rows. Results are computed by SuperQDA itself with the same engine as the web app (identical numbers). Personal-data (pii) and ID columns cannot be selected and are never returned (mixed-methods analyses use the ID column only internally to match participants), and raw rows are never sent.
get_document_content
ChatGPTGet the full text content of a document. Documents are extracted text from PDF/Word files.
get_project
ChatGPTGet details of a specific project including settings and statistics.
get_user_profile
ChatGPTGet the authenticated user's profile information including name, role, subscription plan and expiry, license type, whether Claude/ChatGPT integration (Cloud plan) is enabled, ANKOS license status, and AI credit balance.
list_analyses
ChatGPTList saved analyses (thematic analyses, summaries, etc.) in a project.
list_codes
ChatGPTList all qualitative codes in a project. Codes form a hierarchy (parent-child) and are used to tag text segments.
list_datasets
ChatGPTList the quantitative datasets (Nicel veri, Beta: imported survey/scale tables from CSV, Excel or Google Forms) of a project. Returns id, name, row and variable counts, version, source and the number of linked open-ended documents. Results are computed by SuperQDA itself with the same engine as the web app (identical numbers). Personal-data (pii) and ID columns cannot be selected and are never returned (mixed-methods analyses use the ID column only internally to match participants), and raw rows are never sent.
list_documents
ChatGPTList all documents (PDFs, Word files, texts) in a project. Documents are vectorized and searchable.
list_memos
ChatGPTList analytical memos in a project. Memos are researcher notes attached to documents, codes, or segments.
list_projects
ChatGPTList all qualitative research projects the user has access to in SuperQDA.
list_statistical_analyses
ChatGPTList the statistical and mixed-methods analyses SuperQDA can run (same list as the web app), with names and descriptions in the requested language.
merge_codes
ChatGPTMerge a source code into a target code in the same project: all coded segments, child codes, relations and code memos move to the target, then the source code is deleted. The target must not be a sub-code of the source.
perform_semantic_search
ChatGPTSearch across all project documents using semantic/vector similarity. Returns relevant text chunks ranked by similarity.
perform_text_search
ChatGPTFull-text keyword search across all documents in a project. Returns matches with surrounding context.
save_analysis
ChatGPTSave an analysis result to the project. Used to persist thematic analyses, coding results, or custom analyses.
update_code
ChatGPTUpdate an existing qualitative code: rename it, change its color or type, or move it under another parent code in the code hierarchy. Moving a code under itself or one of its own sub-codes is rejected.
update_coded_segment
ChatGPTChange a coded segment: reassign it to a different code, edit its comment, or set its weight (0-5). Segment IDs come from get_coded_segments.
Capabilities
Writes
