Scoring
Typelets lets you score a candidate against the problem’s rubric criteria, rather than relying on a single gut-feel verdict.
How scoring works
Section titled “How scoring works”A problem defines named criteria (for example “Correctness”, “Communication”, “Code quality”). After the interview, the interviewer scores each criterion on a 1-5 scale with optional notes, plus an overall notes field. Scores are saved on the workspace and visible only to interviewer-side roles.
Scoring is entered by a human. Typelets does not auto-grade - the score is the interviewer’s judgment.
Who can score and see scores
Section titled “Who can score and see scores”- owner / admin / interviewer can enter and view scores.
- candidates and viewers never see the rubric or scores - those fields are stripped before the data reaches them.
A workspace is scorable once it has a prompt and either a rubric or at least one criterion (i.e. a problem has been applied).
LLM-assisted scoring input
Section titled “LLM-assisted scoring input”Through the MCP server, score_against_rubric returns the
recording timeline together with the rubric and criteria, so an AI assistant can
help an interviewer reason about a score. It provides input - it does not
write the score. The final number is always the interviewer’s.
ATS export
Section titled “ATS export”Some deployments can sync the resulting scorecard to an applicant tracking system. This is an optional, deployment-gated integration; if it is not enabled in your deployment, the ATS controls are not present.