# Show HN: Job Finder India – an honest job-fit tool that runs in your AI CLI > Source: > Published: 2026-07-29 13:11:07+00:00 **The job-search tool that tells you the truth about fit — it says "don't apply" when it's a no.** Most AI matchers are optimists: a 70%-there role becomes "4.7/5, great match, here's how to frame your gaps." That wastes your time and the recruiter's. Job Finder India scores each job **0–5** against your résumé, treats a gap in seniority or function as a **disqualifier**, and cites the exact résumé line ↔ job requirement behind every verdict. Fewer, better applications. Runs entirely on your machine. Your résumé never leaves it, and **the app holds no AI API key** — scoring runs inside the AI CLI you already use. ### 👉 New here? Start with [GETTING_STARTED.md](/harshgarg95/job-finder-india/blob/main/GETTING_STARTED.md) — the step-by-step guide. [GETTING_STARTED.md](/harshgarg95/job-finder-india/blob/main/GETTING_STARTED.md) Scoring happens **in-session with your CLI's model**, so the model *is* the scorer. That makes this choice matter more than anything else in setup. | CLI | Status | Notes | |---|---|---| Claude Code | ✅ Recommended | Full flow verified end-to-end. Best verdict quality and multi-step reliability. | GitHub Copilot | Verified in-session. On Free/Student the model is "Auto"-only, which may route to a small model: expect weaker verdicts and occasional partial runs. On paid plans pick GPT-5 or Claude Sonnet/Opus. | | Codex | Its sandbox blocks network by default, so discovery fails (the tool says so loudly rather than reporting "0 jobs"). Enable network access, and prefer a stronger model. | | | opencode · qwen | ▫️ Runs once authed | CLI-agnostic (Bash + files); not as thoroughly exercised. | | Antigravity | ▫️ Desktop app | Legacy Gemini CLI → Antigravity. | A small/default model is a *quality* limit, not a blocker — the tool proceeds either way and warns once. It also refuses to present a partial run as complete: if scoring stops early you get a **"Scored N of M — incomplete"** banner, never a silently short list. ``` git clone https://github.com/harshgarg95/job-finder-india && cd job-finder-india pip install -r requirements.txt python -m jobfinder onboard # one-time setup — asks for your résumé, writes your profile # then open this folder in your AI CLI and say: find me jobs ``` That's the whole interface. Full detail, troubleshooting, and optional API keys are in ** GETTING_STARTED.md**. Review results in the browser at any time: ``` python -m jobfinder dashboard # local page at http://127.0.0.1:8755 (Ctrl-C to stop) ``` **No auto-apply, ever.** It recommends; you decide and click Submit. It never applies for you.**No stealth scraping and no bot-block evasion.** Discovery and JD fetch use free public ATS JSON endpoints — documented APIs for Greenhouse/Lever/Ashby/Workable/SmartRecruiters; for Workday, the same public keyless endpoints its own careers pages use — plus official APIs (Adzuna). If a site blocks automation, it is**detected and skipped**— never worked around.** No credential handling.**It never asks for, stores, or uses your job-board logins. Optional discovery keys live in your own`.env` and are sent only to that provider's API.**No invented experience.** A high score must be earned by evidence already in your résumé.**No spray-and-pray.** It is a filter, not a firehose. The app holds **no scoring API key** — scoring cost is whatever your own AI CLI plan already charges (often zero on an existing subscription; genuinely $0 if you point a local-capable CLI at Ollama). Discovery is free by default: the **public ATS scan needs no key**. Optional channels (Adzuna, JSearch) use *your* free tiers, with a per-run request cap and a persisted monthly counter — when a tier is exhausted or a `429` lands, that channel pauses and discovery degrades to the free floor. Apify deep-mode is **off by default** and bills to your own account if you enable it. Volume is bounded by design: a deterministic prescreen cuts candidates to a few dozen (`config/run.yml` → `prescreen.max_llm_jobs` , default 40) and only the top `scoring.full_score_top_n` (default 15) are fully scored. **A run cannot balloon into thousands of calls.** Every run prints the funnel (`candidates → prescreened → scored` ) and the free-tier left. **Your AI login is never touched.** Scoring runs inside the AI CLI you already use, under that assistant's own login — this tool never sees, stores, or transmits your model credentials, and holds no AI API key of its own.**Job data comes from APIs, not scraping.** Free public APIs — documented ATS APIs, the official Adzuna API; for Workday, the public keyless endpoints its own careers pages use — plus optional third-party APIs you enable with your own keys (JSearch, SerpAPI, Apify) that do their own collection under their own terms. Sites that block bots are**detected and skipped**— never scraped around.** Your résumé, profile, and results stay on your machine.**`resume.md` ,`config/profile.yml` ,`config/preferences.yml` ,`.env` , and everything under`data/` are**gitignored**— never committed, never uploaded. The only content that leaves your computer is the job text your own AI CLI reads in order to score, under that CLI's terms.**Adzuna job links include your Adzuna app id** as a URL parameter — Adzuna requires it for the link to resolve. If you share raw results (`top.md` ,`scored.jsonl` , screenshots) publicly, that id is visible. It is the non-secret half of Adzuna's credential pair; your app key is never written to any file or URL. Full statement: [NOTICE](/harshgarg95/job-finder-india/blob/main/NOTICE) · [DATA_CONTRACT.md](/harshgarg95/job-finder-india/blob/main/DATA_CONTRACT.md). ``` résumé + profile ─▶ DISCOVERY ─▶ dedup + India/keyword filter ─▶ deterministic PRESCREEN (title · seniority · function · location — the volume cap) ─▶ HONEST SCORING in your CLI (prompts/_rubric.md is the law) ─▶ data/results/top.md + data/tracker.md ``` Your CLI reads [ AGENTS.md](/harshgarg95/job-finder-india/blob/main/AGENTS.md) + [and calls small deterministic Python tools (](/harshgarg95/job-finder-india/blob/main/modes) `modes/` `doctor` , `discover` , `prescreen` , `enrich` , `tracker` , `live` ) for the plumbing — then does the judging itself. Nothing is scored that the tool could not actually read: unreadable postings go to a **"Couldn't verify"** bucket instead of being guessed at. **It learns from your corrections.** Mark a role **Applied / Interested / Not suitable (+reason)** in the dashboard (or `python -m jobfinder feedback --job --action wrong_location` ). Corrections persist to `data/feedback.jsonl` , are derived into a preference layer, and replay into the next run's prescreen — already-decided jobs drop out and repeat-rejected patterns are down-ranked (never hidden). The rubric itself never changes. The primary mode is the prompt-pack above. A separate batch path exists for automation: ``` python -m jobfinder doctor # setup check python -m jobfinder --resume resume.md --cli claude # headless ranked top-N ``` Built openly on good prior art, reimplemented from scratch (no copied files): (MIT) — the CLI-agnostic markdown-prompt scoring model, rubric-with-citations, and the User-Layer/System-Layer data contract are inspired by it. Job Finder India deliberately[career-ops](https://github.com/santifer/career-ops)*inverts*its optimistic scoring: where career-ops coaches you to apply, this is built to tell you the honest "no."— the optional BYO-token deep-discovery layer.[Apify](https://apify.com) Independent projects; Job Finder India is not affiliated with or endorsed by them. [MIT](/harshgarg95/job-finder-india/blob/main/LICENSE) © 2026 Harsh Garg.