# itMrBoy/resumePolice

简历警察 🕵️‍♂️ 疯狂逮捕

Repository: https://github.com/itMrBoy/resumePolice
Canonical: https://ross.abutalabs.com/products/resumepolice
License: MIT
License Family: permissive
Last push: 2025-10-09T15:08:29+00:00

## Health v2 (maintenance only)
Score: 39/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 46, release rhythm 35, longevity 28
- inputs: {"age_days": 403, "days_push": 328, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2252, forks 112 (observed 2026-08-28T04:06:31.167660+00:00)

## What it is
A collection of LLM prompts and Dify workflow files for reviewing and improving resumes, plus generating interview questions from an interviewer's perspective. It also links to a transparent GitHub-Issue-based job matching platform.

## Use cases
- review and improve my resume with ai
- generate interview questions for a candidate
- get feedback on my resume before applying
- import a resume review workflow into dify
- find a job by showcasing my open-source work
- optimize my resume for tech roles

## When to choose
- you want AI-assisted resume critique and rewriting
- you use Dify and want ready-made workflow DSL files
- you need structured interview question generation
- you prefer Chinese-language prompts for hiring workflows

## When to avoid
- you need a polished standalone app with a UI
- you need automated resume parsing at scale in production
- you don't use Dify or an LLM API
- you need ATS-compliant resume formatting tools

## Facets
- artifact type: learning-resource
- maturity: active
- function: prompt-engineering, nlp, llm-inference
- domain: artificial-intelligence, large-language-models, hr, developer-tools
- platform: cross-platform
- tags: resume-review, dify-workflow, interview-questions, job-hunting, chinese, prompt-collection, web-server

## Member repositories
- itMrBoy/resumePolice (main) score 39

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:31.167660+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:43:48.983804+00:00, confidence not recorded.
  - readme: https://github.com/itMrBoy/resumePolice (fetched 2026-08-28T04:06:31.167660+00:00, sha d5c8ea6065e6)
- Data as of 2026-08-30T08:39:29.467469+00:00.