| name | lockedin-render-interview |
| description | Drafts an interview answer in English or Korean from the user's
experience. STAR or PAR structure, two-turn writer/reviewer with
a 5-dimension rubric.
Activate when the user says <!-- ko-example -->"interview answer",
"면접 답변", "STAR 답변", "tell me about a time…"<!-- /ko-example -->,
or names a question and asks for an answer.
|
render-interview
Status: v1.2 (calibrated). Research-based calibration complete.
RUBRIC.md ships with five cross-source-validated dimensions. A
banned_phrases.json (25 entries, each backed by 2+ sources) and
research-notes.md (7 cited sources) ship alongside the prompts.
Pass/fail fixture corpus under tests/fixtures/interview/.
Use this when
- The user names an interview question and asks for an answer.
- The user pastes a job description and asks for talking points.
- The user says "STAR" or "behavioural" or "면접" or "기술 면접".
Do NOT use when
- The user wants a full resume →
lockedin-render-resume-en.
- The user wants a Korean cover letter →
lockedin-render-jaso.
- The vault has no relevant role / project / achievement nodes.
Seed first via
/lockedin init or by ingesting a resume.
Two-turn pattern
Writer turn produces the draft. Reviewer turn re-loads RUBRIC.md
fresh in a separate Claude turn and emits a JSON score. Same as the
other renderers; the split is load-bearing.
Output shape
A single markdown answer, no headers. STAR (Situation / Task /
Action / Result) by default; PAR (Problem / Action / Result) when
the question is incident-shaped. One experience per paragraph with
explicit transitions, mirroring the policy in
lockedin-render-resume-en and lockedin-render-jaso.
The answer pulls evidence from the vault using slug citation
([[type/slug]]); the slugs are resolved to natural language by
lockedin/render/resolve_slugs.py before the artifact is shown to
the user.
Files in this directory
SKILL.md (this file)
research-notes.md 7 cited sources, cross-source analysis summary
banned_phrases.json 25 entries, severity-tagged, each backed by 2+ URLs
prompt-writer.md writer-turn instruction
prompt-reviewer.md reviewer-turn instruction (re-loads RUBRIC.md fresh)
RUBRIC.md 5-dimension scoring contract + score bands
Calibration status
v1.2 calibrated. The rubric dimensions (clarity, evidence_density,
persona_fit, conciseness, tone) are grounded in cross-source public
research from MIT CAPD, The Muse, Indeed, Harvard Business Review,
Yale OCS, The Interview Guys, and Big Interview. The banned_phrases.json
contains 25 entries across four categories (weak_ownership, trait_claim,
rehearsed_non_answer, vague_filler), each backed by 2+ independent
sources. Pass and fail fixture corpus is at
tests/fixtures/interview/{pass,fail}/ (3 pass, 3 fail).
