stu

Launches a local traceability app verifying research tags and findings against transcript lines.

1|Updated May 29, 2026
One-click install
npx skills add https://github.com/borderux/recursica-knowledge --skill stu-borderux
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stu
Source: https://github.com/borderux/recursica-knowledge/tree/main/agents/stu
Command: npx skills add https://github.com/borderux/recursica-knowledge --skill stu-borderux

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Qualitative research produced by AI analysis is hard to trust: tags, dictionary terms, and findings may not trace back to real transcript lines, and there is no easy way for a person to check the work or record corrections. Stu solves this by launching a local web app that lets a human verify every claim against its source line and records each human edit against a named identity. ## Core Features & Use Cases - Traceability Explorer: Launches a local web app where every tag, dictionary term, and finding links back to the exact transcript line it came from. - Human Decision Queue: Reports what is waiting on a person — terms and findings sitting at proposed, untagged lines, count mismatches, and thin evidence — pulled from BigQuery before handoff. - Attributed Edits: Records every human edit in edit_log against a verified identity (Buzz pubkey or email), while the agent itself never edits or approves anything. - Use Case: After Claire ingests and analyzes interview transcripts, Stu launches the explorer, hands the reviewer a localhost URL, and summarizes which proposed terms and findings need a human decision. ## Quick Start Ask Stu to launch the traceability explorer for your research project and report which proposed terms and findings are waiting for review.

Frequently Asked Questions about stu

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I verify AI-generated research findings against interview transcripts?▼

Launch the traceability explorer, which links every tag, dictionary term, and finding back to the exact transcript line it came from. A person reviews the evidence in the web app and approves or edits items, with each change recorded against their identity.

How do I launch the Stu traceability app?▼

Run ./start.sh --user-email <email> --user-name "<name>" from the app directory, with slug, project, and service-account key configured in stu.env. The command is idempotent and prints a localhost URL to share with the reviewer.

Can Stu edit or approve research data directly?▼

No. Stu never edits data and never moves items from proposed to active — only a human does that through the app. On Claude Code this is enforced by connecting Stu to a read-only BigQuery server rather than relying on prompt instructions.

What access does Stu need to BigQuery?▼

Stu needs the same per-project fenced BigQuery access as Claire, using a read-only MCP server scoped to one project's dataset. The service account and allowedDatasets fence provide the isolation, not the prompt.

Why is opencode not a supported target for Stu?▼

opencode's agent model uses a coarse permission block with no per-tool allowlist, so it cannot enforce read-only BigQuery access. Stu's core guarantee — that he never writes to the data — would have nothing behind it on that platform.