Alternatives
Products that do what JD Intelligence — Job Description API does
Turn any job posting into structured JSON, one API all
- 1JB
2015 · github.com
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Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…
2025 · github.com
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Hello! I used an LLM to extract structured data from each comment on the “Ask HN: Who is Hiring? (January 2024)” post, available at: https://news.ycombinator.com/item?id=38842977. This created a dataset of 400+ jobs with data such as title, company name, location, is job remote, salary data, and the URL/email to contact. For the UI, a NextJS static site was created to filter and view the structured data.
2024 · hnjobsai.vercel.app
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Hey HN! I'm excited to show off this side project I've been working on. This project matches your resume with the best matching jobs from the monthly HN Who's Hiring post. It works by creating a vector embedding of your resume using OpenAI's embedding API, and then ranking the jobs using a vector similarity score. (You can toggle between max inner product, cosine, and euclidean in the "Advanced Options") I was laid off in August and it took a whole 6 months for me to find my new job. Fortunately, I found my new role on January's HN Who's Hiring post. So I hope this will prove useful to any…
2023 · hnresumetojobs.com
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Rewrite and add to your job descriptions with OpenAI's GPT-3
2020
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There are existing HN job aggregators, but I thought we could take it a step further. Inspired by an insightful comment on a previous thread (https://news.ycombinator.com/item?id=36163021), I built a tool that aggregates job postings and intelligently categorizes them based on user-specific preferences: * Country and remote work preferences * Employer type (e.g., startup, corporation, government) * Industry * Technologies used * Role type (developer, architect, product owner, etc.) * Salary range (where available) One of the superpowers of LLMs is reformatting information from…
2023 · kadoa.com
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Generate perfect job descriptions for any role in seconds
2023
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When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai
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2021 · jsonme.com
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Author here! Agents are applying to jobs for people right now, with progressively more volume, and there's nothing built for it. So they scrape career pages and fight ATS forms with Playwright/Browser Use, which breaks constantly (or they get bot blocked). Employers get buried in applications that don't fit, candidates hear nothing back, and the resume is now an AI-written thing that another AI scores (which breaks the existing model entirely, btw). OJCP is MCP tools for search and apply, a manifest at /.well-known/ojcp.json so agents can find providers, and schemas that…
25d ago · ojcp.dev
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Use this site to get an evaluation of how well you fit a job description given your resume, cover letter (optional), and GitHub (optional) This is my first side project so any feedback would be awesome!
2025 · coderview-ai.com
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Hey HN! Erik here from banana.dev We’ve trained a small(ish) language model on structured extraction, and today we’re launching a playground for it at https://anythingtojson.com. Give it a try! This model continues our work on structured generation, following last week’s launch of Fructose[1], a python client for strongly-typed LLM responses. There seem to be two distinct halves of the problem intended to be solved by Fructose and structured generation: 1. the reasoning ability of the model, such as performing chain of thought, creative acts, and natural language tasks. In a way,…
2024 · anythingtojson.com
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