discover-industrial-opportunities

americanreindustrialization.com/discover-industrial-opportunities-tdvqp0 · updated May 21, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$browse install americanreindustrialization.com/discover-industrial-opportunities-tdvqp0
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summary

Discover companies, startups, suppliers, and job opportunities across American reindustrialization — manufacturing, energy, defense, aerospace, robotics, semiconductors, and industrial software — via the site's public JSON REST API at /api/* (companies, jobs, categories, tags).

skill.md
name
discover-industrial-opportunities
title
American Reindustrialization — Discover Companies & Jobs
description
>- Discover companies, startups, suppliers, and job opportunities across American reindustrialization — manufacturing, energy, defense, aerospace, robotics, semiconductors, and industrial software — via the site's public JSON REST API at /api/* (companies, jobs, categories, tags).
website
americanreindustrialization.com
category
directory
tags
- reindustrialization - manufacturing - jobs - companies - directory - industrial - supply-chain
source
'browserbase: agent-runtime 2026-05-19'
updated
'2026-05-19'
recommended_method
api
alternative_methods
- method: browser rationale: >- Fallback only — the site is a React SPA so any browser-driven step pays a hydration tax for data the JSON API already returns whole. Use scripted browsing only if /api/* ever starts 4xx-blocking; deep-link to /companies?category=&state=, /categories/{slug}, /tags/{slug}, /jobs/c/{cat}, /companies/{slug}, /jobs/l/{slug}. - method: url-param rationale: >- Useful for human / agent browsing — front-end URLs /companies?category=&state=, /jobs?category=&tag=, /categories/{slug}, /tags/{slug}, /jobs/c/{cat-slug} are deep-linkable, but ?company=, ?job_type=, ?work_mode=, ?location=, ?experience= do NOT filter (UI-state only).
verified
true
proxies
true

American Reindustrialization — Discover Industrial Opportunities

Purpose

Discover companies, startups, suppliers, and job opportunities shaping the American reindustrialization wave on americanreindustrialization.com — a curated public directory spanning manufacturing, defense & security, energy, technology, materials & metals, aerospace, autonomous systems, industrial automation, logistics, supply chain, AI, and industrial software. Returns structured records: companies (logo, tagline, descriptions, HQ city/state, sector, tags, employee range, funding stage, founded year, careers email, website, jobs count) and jobs (title, description, employer, location, work mode, employment type, experience level, posting date, salary when published, and the external apply_url pointing to the employer's own ATS — Lever / Greenhouse / Ashby). Read-only; never submits, applies, or POSTs.

When to Use

  • Bulk extraction of every company in a sector (e.g. "all U.S. fusion-energy companies", "all CNC machining suppliers", "all defense-tech startups in Texas").
  • Job hunting / market mapping — "all senior roles in aerospace", "all on-site jobs in manufacturing posted in the last 30 days", "all open roles at Last Energy".
  • Investor / corp-dev sourcing — enumerating early-stage reindustrialization companies by funding stage, sector, or geography.
  • Building downstream tooling (newsletters, Slack feeds, dashboards) that watches the directory for new entries.
  • Tag-based discovery (e.g. made-in-usa, fusion-energy, evtol, cnc-machining, sheet-metal-fabrication, predictive-maintenance).

Workflow

The site is a Vite/React SPA, but its content is served by a clean public JSON REST API at https://americanreindustrialization.com/api/*no auth, no cookies, no anti-bot stealth, no rate-limit headers observed. The API is the canonical path; scripted browsing is strictly the fallback (the SPA shell is empty <div id="root"></div> until JS hydrates, so every browser-driven step pays a render-tax for data the API hands back in milliseconds). Cloudflare fronts the site but does not challenge the API. A residential proxy is not required.

1. Pick the right list endpoint

QuestionEndpoint
"Show me companies"GET /api/companies
"Show me one company"GET /api/companies/{slug}
"Show me jobs"GET /api/jobs
"Show me one job"GET /api/jobs/{title-slug}-{8charId}
"Enumerate every category"GET /api/categories (44 items, all-time) or GET /api/jobs/categories (15 items, only categories with ≥1 active job; each includes jobs_count)
"Enumerate every tag"GET /api/tags (87 items, all-time) or GET /api/jobs/tags (29 items, with active jobs)
"Enumerate companies that have jobs"GET /api/jobs/companies[{id, name}], 20 items
"Autocomplete job titles"GET /api/jobs/titles — array of 403 distinct title strings

All list responses have the shape {"data": [...], "total": N, "page": 1, "limit": 20, "totalPages": K}. Detail endpoints return the bare object (no envelope). Enum endpoints (/api/categories, /api/tags, /api/jobs/categories, /api/jobs/companies, /api/jobs/tags, /api/jobs/titles) return a bare JSON array — no envelope, no pagination.

2. Filter /api/companies

Append as query string. Multiple filters combine with AND.

ParamValuesNotes
pageinteger ≥ 1Default 1.
limitinteger (server caps at ~100)Default 20. Use limit=100 for fewer round-trips.
categorycategory slug (e.g. manufacturing)Single-value. Categories live at /api/categories.
statetwo-letter US state (e.g. CA, TX)Matches hq_state. Param is state, not hq_state.
queryfree-textMatches name / tagline / description. Param is query, not q or search.
statuspublishedCritical: the unfiltered total is 96, but only 68 are publicly published — the UI's /companies page filters to status=published. Add this for UI parity.

3. Filter /api/jobs

ParamValuesNotes
page / limitas aboveTotal job pool was 501 at survey time.
categorycategory slug (manufacturing, aerospace, energy, …)Single-value.
tagtag slug (fusion-energy, made-in-usa, evtol, …)Single-value.
company_idUUID (e.g. a1ba45d1-3e7e-429c-8e13-3eb19eb4b3bc)Critical: filter by company ID only, not slug or display name. Resolve the UUID first via /api/companies/{slug}.id or /api/jobs/companies.
job_typefull-time / internship / part-time / contractkebab-casefull_time returns 0.
work_modeon-site / remote / hybridon-site is hyphenated.
experience_levelentry / mid / senior / leadParam is experience_level, not experience or level.
queryfree-textSearches title + description.

4. Walk pagination

GET /api/companies?status=published&limit=100&page=1   # → 68 results, totalPages=1
GET /api/jobs?limit=100&page=1                          # → 100/501
GET /api/jobs?limit=100&page=2                          # → next 100
…until page > totalPages

A Referer header is not required. No auth. Keep a courteous ≤ 2 req/s.

5. Read individual records

  • GET /api/companies/{slug} returns the full company object — same field set as list items plus full categories[], tags[], company_categories[] (with is_primary), and products_services array.
  • GET /api/jobs/{title-slug}-{8charId} returns the job with an embedded company object and the external apply_url (almost always an ATS URL like https://jobs.lever.co/..., https://boards.greenhouse.io/..., or https://jobs.ashbyhq.com/...).

The slug for a job is e.g. radar-intern-632a1249 — title-kebab + hyphen + an 8-char hex id. Get the slug from the list response's slug field, or from /companies/{slug} pages on the front-end (/jobs/l/{slug} href).

6. Resolve image URLs verbatim

logo_url / cover_image_url are pre-built absolute URLs on the img.americanreindustrialization.com CDN, the legacy americanreindustrialization.com/storage/... path, the company's own domain, or framerusercontent.com. Use them as-is.

Browser fallback

If the API ever returns 403/5xx (none observed during survey), drive the SPA directly:

  1. browse open https://americanreindustrialization.com/{path} — wait ~2-3s for hydration; the bare HTML is empty until React mounts.
  2. The following front-end URLs are deep-linkable and do honor URL params:
    • /companies?category={slug}&state={XX} — directory filter (note: front-end UI shows status=published data only).
    • /categories/{slug} — full company list for one category (single page, no pagination control).
    • /tags/{slug} — full company list for one tag.
    • /jobs?category={slug} — paginated job board, filtered by category.
    • /jobs?tag={slug} — paginated job board, filtered by tag.
    • /jobs/c/{category-slug} — single-page job list for one category (e.g. /jobs/c/aerospace → 99 listings; no pagination control).
    • /jobs/l/{slug} — single job detail; the green Apply on Company Site anchor's href is the same apply_url field.
    • /companies/{slug} — single company detail with sidebar View All Jobs at {Company} link.
  3. browse get markdown body after each navigation; harvest data from the rendered text. The page-rendered text mirrors the API fields 1:1.
  4. Do not attempt URL filters that the SPA reads only from in-page state — these are dead in the URL: ?company=<anything>, ?job_type=, ?work_mode=, ?location=, ?experience=, ?min_salary=, ?posted=, ?position=. They appear in the homepage's "X open roles" anchors (/jobs?company=anatar) but do not filter the list — they just navigate to the unfiltered job board. Use the API's company_id (UUID) instead.

Site-Specific Gotchas

  • Public JSON API at /api/* is the canonical surface. Do not scrape the React-rendered HTML when the API can answer in one request. There is no anti-bot challenge on the API; no auth, no cookies, no Referer requirement. Cloudflare sits in front (Cf-Ray, Server: cloudflare) but does not block direct fetches.
  • /api/companies total = 96 but /companies UI shows 68. The unfiltered API includes drafts / unpublished records. Add ?status=published (or ?published=true) to match the public catalog. This is the single most common mistake — leaving it off yields ~30% phantom records with stale or null fields.
  • /api/jobs?company={name} and ?company_slug={slug} are silently ignored — they 200 with the unfiltered 501-job pool. Only company_id={uuid} filters. To find the UUID: GET /api/companies/{slug}.id, or page through /api/jobs/companies (only 20 employers have active listings). Hardcoding company slugs in your filter logic will produce false-positive "all 501 jobs match this company" bugs.
  • Filter param names are non-obvious. Companies use state= (not hq_state=) and query= (not q= or search=). Jobs use experience_level= (not experience= or level=) and job_type= in kebab-case (full-time; full_time returns zero). Unrecognized params are silently dropped — a 200 OK with total=501 always means "your filter didn't apply", never "no matches".
  • work_mode=on-site is hyphenated. Enum values for work_mode: on-site (492), remote (6), hybrid (3). For experience_level: entry (18), mid (458), senior (21), lead (~4). For job_type: full-time (484), internship (15), part-time (1), contract (1).
  • Front-end URL filters that DON'T work in the URL bar. The /jobs filter sidebar (Company, Position, Job Type, Work Mode, Experience, Location, Minimum Salary, Posted, Tag) is mostly UI-state only. Only ?category=, ?tag=, and the search-bar q= propagate to URL. The other dropdowns mutate React state and do not produce shareable / scriptable URLs — even though the homepage's "X open roles" badges link to /jobs?company=<slug> URLs, those don't actually filter the displayed list. Always use the JSON API for non-category/tag job filtering.
  • /categories/{slug} and /jobs/c/{cat-slug} render full lists on a single page, no pagination. /companies and /jobs (the global views) do paginate (20 per page front-end, configurable up to ~100 on the API).
  • jobs_count on company records is often 0 because most companies in the directory don't post jobs through the platform — only ~20 employers have active listings. Use /api/jobs/companies to enumerate hiring employers cheaply rather than counting company-by-company.
  • apply_url points off-site. Every job's apply flow exits to the employer's own ATS (Lever, Greenhouse, Ashby, etc.). The site does not collect applications — never POST anywhere on americanreindustrialization.com for job applications.
  • /api/news and /api/blog exist but currently return empty arrays ([]). Don't rely on them for content discovery yet.
  • /api/states returns 404. No public enum endpoint for U.S. states; use a hardcoded list of two-letter abbreviations when needed, or harvest the distinct hq_state values across /api/companies.
  • robots.txt is restrictive for AI crawlers — Cloudflare-managed Content-Signal: search=yes, ai-train=no and explicit Disallow: / for ClaudeBot, GPTBot, CCBot, Google-Extended, Bytespider, Applebot-Extended, Amazonbot, CloudflareBrowserRenderingCrawler. Honor it for compliant operation. The API does not check User-Agent; observed requests succeed regardless, but the site has expressly reserved AI-training rights under the EU Article 4 opt-out signaled in the robots header.
  • Sitemap.xml is the cheap enumeration backstop. https://americanreindustrialization.com/sitemap.xml (~170 KB) lists every /companies/{slug}, /categories/{slug}, /tags/{slug}, and /jobs/c/{cat} URL — but does NOT list individual job-listing URLs (/jobs/l/...) or tag-scoped job views (/jobs/t/...). For job enumeration, walk /api/jobs pagination instead.
  • No rate-limit headers were observed, but be courteous. Cloudflare is in front; aggressive bursts will earn 429s. ≤ 2 req/s sustained, batched paginated calls (limit=100) is the polite path.

Expected Output

Shape A — paginated company list (GET /api/companies?status=published&category=manufacturing&limit=100)

{
  "data": [
    {
      "id": "a1c19858-1eda-4bff-a0cb-d6f94ab9d3f7",
      "name": "Harmony AI (tryharmony.ai)",
      "slug": "harmony-ai",
      "tagline": "AI Automation for Manufacturing",
      "short_description": "Harmony AI provides an AI-native operating system that connects plant data...",
      "full_description": "Harmony AI is an AI-native operating system designed specifically for American manufacturing...",
      "website_url": "https://tryharmony.ai",
      "logo_url": "https://img.americanreindustrialization.com/company-assets/a1c19858-.../kt5XHThBvsz7....jpg",
      "hq_city": null,
      "hq_state": null,
      "hq_country": "United States",
      "founded_year": null,
      "employee_range": null,
      "funding_stage": null,
      "primary_sector": null,
      "is_us_based": true,
      "status": "published",
      "published_at": "2026-04-22T17:33:11.000000Z",
      "careers_email": null,
      "products_services": [],
      "jobs_count": 0,
      "categories": [
        { "id": "6e1ee891-...", "name": "Manufacturing", "slug": "manufacturing", "pivot": { "is_primary": 1 } }
      ],
      "tags": [
        { "id": "5923c8a5-...", "name": "AI & Machine Learning", "slug": "ai-machine-learning", "tag_type": "tech" }
      ]
    }
  ],
  "total": 36,
  "page": 1,
  "limit": 100,
  "totalPages": 1
}

Shape B — paginated job list (GET /api/jobs?category=aerospace&job_type=full-time&limit=100)

{
  "data": [
    {
      "id": "a1ba48c9-c18b-4bf4-9945-f82f1af481e5",
      "company_id": "a1ba45d1-3e7e-429c-8e13-3eb19eb4b3bc",
      "title": "Research Engineer, Aerosol & Liquid Dispersion Systems",
      "slug": "research-engineer-aerosol-liquid-dispersion-systems-9601c64b",
      "description": null,
      "job_type": "full-time",
      "work_mode": "on-site",
      "location_city": "El Segundo",
      "location_state": "CA",
      "location_country": "United States",
      "salary_min": null,
      "salary_max": null,
      "salary_currency": null,
      "salary_period": null,
      "experience_level": "mid",
      "apply_url": "https://jobs.lever.co/make-rain/...",
      "status": "published",
      "posted_at": "2026-05-08T04:31:23.000000Z",
      "expires_at": null,
      "is_auto_fetched": true,
      "company": {
        "id": "a1ba45d1-3e7e-429c-8e13-3eb19eb4b3bc",
        "name": "Rainmaker",
        "slug": "rainmaker",
        "logo_url": "https://img.americanreindustrialization.com/company-assets/.../dpyvw....jpg",
        "tagline": "Make rain. Make snow. Make..."
      }
    }
  ],
  "total": 73,
  "page": 1,
  "limit": 100,
  "totalPages": 1
}

Shape C — single company (GET /api/companies/relativity-space)

{
  "id": "...",
  "name": "Relativity Space",
  "slug": "relativity-space",
  "tagline": "...",
  "short_description": "...",
  "full_description": "...",
  "website_url": "https://www.relativityspace.com",
  "hq_city": "...",
  "hq_state": "...",
  "categories": [ { "name": "Aerospace", "slug": "aerospace", "pivot": { "is_primary": 1 } } ],
  "tags": [ { "name": "Space", "slug": "space" },],
  "products_services": ["Terran R", "Stargate 3D printer",],
  "jobs_count": 0,
  "careers_email": null
}

Shape D — single job (GET /api/jobs/radar-intern-632a1249)

{
  "id": "...",
  "company_id": "a1ba45d1-...",
  "title": "Radar Intern",
  "slug": "radar-intern-632a1249",
  "job_type": "internship",
  "work_mode": "on-site",
  "location_city": "Norman",
  "location_state": "OK",
  "experience_level": "entry",
  "apply_url": "https://jobs.lever.co/make-rain/58c47b24-5e07-4c40-84ca-046c040f5131",
  "posted_at": "2026-05-08T04:31:23.000000Z",
  "company": { "id": "...", "name": "Rainmaker", "slug": "rainmaker", "logo_url": "...", "tagline": "..." }
}

Shape E — taxonomy enum (GET /api/categories, GET /api/tags, GET /api/jobs/categories)

[
  {
    "id": "6e1ee891-4ade-4559-9ef4-56299c1c39aa",
    "name": "Manufacturing",
    "slug": "manufacturing",
    "description": "Companies involved in industrial manufacturing and production",
    "parent_id": null,
    "sort_order": 1,
    "image_url": null,
    "jobs_count": 253
  }
]

(Top-level array, no envelope, no pagination. jobs_count present only on /api/jobs/categories and /api/jobs/tags. tag_type present only on /api/tags and /api/jobs/tags — observed values include tech, industry, and others.)

how to use discover-industrial-opportunities

How to use discover-industrial-opportunities on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add discover-industrial-opportunities
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$browse install americanreindustrialization.com/discover-industrial-opportunities-tdvqp0

The skills CLI fetches discover-industrial-opportunities from GitHub repository americanreindustrialization.com/discover-industrial-opportunities-tdvqp0 and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/discover-industrial-opportunities

Reload or restart Cursor to activate discover-industrial-opportunities. Access the skill through slash commands (e.g., /discover-industrial-opportunities) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.755 reviews
  • Kabir Smith· Dec 28, 2024

    We added discover-industrial-opportunities from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chinedu Lopez· Dec 28, 2024

    Solid pick for teams standardizing on skills: discover-industrial-opportunities is focused, and the summary matches what you get after install.

  • Sakura Tandon· Dec 16, 2024

    discover-industrial-opportunities is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Dec 4, 2024

    discover-industrial-opportunities reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Isabella Zhang· Dec 4, 2024

    discover-industrial-opportunities reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yash Thakker· Nov 23, 2024

    I recommend discover-industrial-opportunities for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Isabella Anderson· Nov 23, 2024

    I recommend discover-industrial-opportunities for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kabir Gonzalez· Nov 19, 2024

    Keeps context tight: discover-industrial-opportunities is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Neel Chen· Nov 7, 2024

    discover-industrial-opportunities fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chinedu Bhatia· Nov 7, 2024

    discover-industrial-opportunities has been reliable in day-to-day use. Documentation quality is above average for community skills.

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