avabbbb/offeru/interview-scoring
Claude Code and agent skill by avabbbb/offeru
- community
Checking that the SKILL.md file is still in the repository.
Score mock-interview answer content with a versioned declarative rubric, persist reproducible evidence, and report locally derived delivery events separately. Use for AI interview evaluation, custom interview rubrics, answer feedback, and body-language event summaries.
Install
npx vskill@latest install avabbbb/offeru/interview-scoringSKILL.md
Interview Scoring Skill
Use the rubric in references/default-rubric.json unless the interview pins another validated version.
Workflow
- Resolve the pinned
skill_idandversion. - Evaluate answer content only from the question, answer, verified career evidence, and job dossier.
- Require answer excerpts for every scored dimension.
- Compute the weighted content score deterministically; never accept a model-provided total.
- Keep delivery events in a separate summary of counts, duration, confidence, and detector version.
- Persist the rubric version, input hash, model runtime, content result, and delivery summary.
- Emit a learning observation; never write interview feedback directly into Profile.
Custom Rubric Guide
Default rubric: references/default-rubric.json. Customize only when the pinned skill does not fit the target role or goal.
Draft a rubric (no write)
Run the draft_interview_scoring_skill operation through the Operation Registry:
goal(required): what the rubric should score.target_role(optional): role label to scope the dimensions.job_id(optional): injects the role dossier'sinterview_process/interview_question/role_requirementfindings as dimension-design input when that job was researched.
The operation returns a draft only — it never persists. The draft must pass validate_scoring_skill_definition (retried once with the error); a second failure raises and returns no draft.
Promote the draft (HITL)
Only after explicit user confirmation, call create_interview_scoring_skill with skill_id, name, and definition=<draft>. Confirmation is proven by the authorized run step (_validate_authorization); the operation takes no user_confirmed argument.
Draft constraints
- Dimensions are weighted within the schema; aggregation is
weighted_mean; every scored dimension requires answer excerpts. score_bands: 2–8 bands,mindescending, and amin=0fallback band is mandatory.behavior_displayis the only optional top-level key and is display-only: it selects which delivery-behavior panels the report renders and never feeds the content score.- Prohibited outputs and delivery-term red lines still apply to the draft.
Boundaries
- Do not execute Python, JavaScript, Shell, plugins, or undeclared dependencies from a rubric.
- Do not combine content and delivery into one score.
- Do not infer personality, emotion, honesty, health, protected traits, job fitness, hiring probability, or cultural fit from camera, gesture, posture, face, or voice signals.
- Do not store raw audio, video, screenshots, frames, landmarks, or face embeddings.
- Do not invent scores or return success after invalid model output.
- Use the Operation Registry for every read or write.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingbackend/app/agents/skills/interview-scoring/SKILL.md
Popularity
- Repository stars
- 23
- Repository forks
- 4
- 7-day trend score
- 0
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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