Mot: a career coach that grades your interview answers against O*NET, not vibes

Description and use

Mot is a career assistant that uses structured O*NET data to provide evidence‑based career exploration, mock interview coaching with objective grading, and an interest quiz that matches users to occupations.

Problem

Career advice often relies on unverified, vague answers; users need data‑driven guidance that cites authoritative sources.

Outcome

Mot delivers structured, source‑backed career exploration, mock interview coaching with objective grading, and an interest quiz that matches users to occupations based on deterministic RIASEC scoring.

Workflow

• 1. User selects an agent (/explore, /interview, /quiz).
• 2. Agent queries the O*NET dataset via Sanity Context MCP endpoints.
• 3. For interview coaching, the agent retrieves a job brief and relevant coaching guides, then asks questions and grades answers using level‑scale anchors.
• 4. Results are presented with source links and a final report.
• 5. Users can bookmark occupations and compare them side‑by‑side.

Evidence

Mot has three agents, each on its own page: Career Explorer, Mock Interview Coach, Interest Quiz.

Source

Interview grading uses Level Scale Anchors. O*NET doesn’t just say Programming matters for Software Developers. It says the job needs Programming at level 4.x on a 0–7 scale, and it publishes concrete anchors for levels 2, 4, and 6.

Source

Career moves are computed, not guessed. compareOccupations diffs the rating arrays of two occupations and returns the skill, knowledge, and ability gaps, the shared strengths, the Job Zone change, and the new technologies.

Source

The rating card is a client‑side tool. The server reads the ratings from the UI messages and scores them in code: each RIASEC type gets 1 + 6 × mean, the same 1–7 scale O*NET uses for occupations.

Source