.claude/skills/mock-interviewRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
基于用户真实经历的模拟面试。引导录入经历后生成 5 道深挖题,在本地网页答题(支持语音),答完按 5 个维度打分并生成评分报告。当用户想练面试、模拟面试、准备面试、练习行为面试题时使用。
These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.
These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.
.claude/skills/mock-interviewRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/mock-interviewRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/mock-interviewRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.
clawhub install @2641183145-oss/mock-interviewclawhub inspect @2641183145-oss/mock-interview --version 1.0.0This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.
This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.
The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.
sha256:4108eb18d8381f2d07b1b9cf6e7a6ca048016b40c567a2c8cf7f5dfd19edf179__pycache__/console.cpython-314.pyc.gitignoreapi-contract.mdbuild_report.pyconsole.pydata/scores.example.jsondata/session.example.jsonLICENSEREADME.mdreferences/intake.mdreferences/question-gen.mdreferences/rubrics.mdserver.pyskill-card.mdSKILL.mdsmoke_test.pytest_partial.pytest_validation.pyverify_depth.pyverify_report.pywait.pyweb/index.htmlweb/score-report.template.htmlInitial release: structured, experience-driven mock interview with automatic scoring and feedback. - Guides users through 4 steps: experience intake, custom question generation, web-based answering, and detailed scoring report. - All questions cite user's real experiences and responses, avoiding generic or invented content. - Scoring and feedback are structured in 5 dimensions, with actionable, non-generic suggestions and rewrite examples. - Built-in scripts manage each stage—data intake, web server, waiting for user answers, scoring, and HTML report generation. - Designed for concise, referenceable user interactions; all files and steps clearly documented. - No user content is invented; all feedback is grounded in actual user input and performance.