# interviewstreet/hiring-agent

AI agent to evaluate and score resumes.

Repository: https://github.com/interviewstreet/hiring-agent
Canonical: https://ross.abutalabs.com/products/hiring-agent
Language: Python
License: MIT
License Family: permissive
Last push: 2026-07-27T12:59:43+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 94, release rhythm 35, longevity 28
- inputs: {"age_days": 401, "days_push": 37, "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 7007, forks 1377 (observed 2026-08-28T04:09:53.200908+00:00)

## What it is
An open-source AI agent pipeline from HackerRank that extracts structured data from resume PDFs, enriches it with GitHub signals, and produces explainable resume scores using locally-run LLMs via Ollama. It is a CLI tool for ranking large volumes of applications, not a full applicant tracking system.

## Use cases
- score and rank resumes automatically
- parse resumes from pdfs into structured data
- screen high volumes of intern applications
- evaluate candidates with local llm models
- enrich resume evaluation with github activity signals
- get explainable candidate scoring

## When to choose
- you receive thousands of resumes and need to prioritize which to read first
- you want a self-hosted, privacy-friendly resume screener with no cloud API keys
- you need explainable, category-level scoring rather than a black box
- you want to enrich resume data with public GitHub signals

## When to avoid
- you need a full applicant tracking system with pipelines and interview scheduling
- you want zero score variance - LLM scoring is inherently non-deterministic
- you need production-grade hiring decisions without human review
- you require a polished product for customers rather than a demo-grade pipeline

## Facets
- artifact type: cli-tool
- maturity: active
- function: agent-framework, llm-inference, nlp, ocr, pdf, parser, cli
- domain: artificial-intelligence, large-language-models, hr, developer-tools
- platform: python, cli, cross-platform, self-hosted
- tags: resume-scoring, resume-parsing, hiring, recruiting, ollama, github-enrichment, explainable-ai, candidate-ranking, ai-agents, natural-language-processing

## Member repositories
- interviewstreet/hiring-agent (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:53.200908+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 2026-08-29T17:40:44.553743+00:00, confidence not recorded.
  - readme: https://github.com/interviewstreet/hiring-agent (fetched 2026-08-28T04:09:53.200908+00:00, sha 23e234d66bde)
- Data as of 2026-08-30T08:39:29.467469+00:00.