linkme/CLAUDE.md

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Commands

command	what it does
bun fetch	run all searches in config.ts, append new jobs to results/jobs.csv
bun recheck	fetch in raw mode, list filtered-out jobs + word-frequency keyword suggestions

Temp scripts: bun run scripts/<name>-temp.ts — never edit config.ts for one-off searches.

Structure

config.ts          # search keywords and areas
fetch.ts           # scraper, HTML parser, all filters
fetch-other.ts     # extra sources (datacareer.ch, stellen-basel.ch, itjobs.ch, job-room.ch, Basel intl orgs)
index.ts           # orchestrator: runs searches, writes CSV
recheck.ts         # raw-mode fetch, lists filtered-out jobs
scripts/           # one-off search scripts; import from ../config.ts and ../fetch.ts
cv/polo.md         # Rafael's profile — use for ranking jobs
cv/                # CV files (html, pdf, odt)
results/jobs.csv   # output — one row per job
jobs/              # notes on specific job leads
plans/             # LinkedIn post drafts

Architecture

• config.ts — KEYWORDS string (joined with OR) and searches: SearchConfig[]. Edit here to add/remove search areas or keywords.
  • Also exports PLATFORM_KEYWORDS (architect/SRE/infra/security/MLOps), RESEARCH_KEYWORDS (research & scientific software, HPC, data platform) and FIELD_KEYWORDS (forward-deployed, customer/sales/integration, founding/product). Kept as separate OR-strings rather than folded into KEYWORDS — LinkedIn ranks a focused query far better than one 50-term disjunction. The sweep() helper generates one search per area per family; Research skips Bern, Platform and Field add a Switzerland-wide remote pass.
  • RESEARCH_KEYWORDS deliberately contains no bioinformatics/computational-biology terms — see BIO_DOMAIN_RE.
• fetch.ts — HTTP scraping, HTML parsing, and all filters. Exports fetchJobs(config, { raw? }) and isEnglishContent(id).
• fetch-other.ts — scrapes extra sources (datacareer.ch, stellen-basel.ch, itjobs.ch, job-room.ch, Basel international orgs). Imported by index.ts.
  • datacareer.ch currently returns 403 on every page — the source is dead and yields nothing. Needs new headers or a different entry point.
  • Basel international orgs (fetchBaselIntlOrgs) sweeps three boards under one label, each only a handful of postings:
    • BIS — the career site is JS-rendered with no usable API, so we read the UNjobs mirror at unjobs.org/offices/bis_182320855689338880. Titles arrive as Role, City, Country and get split back apart. BIS also cycles Senior Software / Data / Data & Analytics Engineer roles through this board.
    • Swiss TPH — Umantis at jobs.swisstph.ch/Jobs/All. Site chrome is German even on English postings, so isEnglishUrl would reject everything; contentChecked: true and the title filters decide instead.
    • Basel Institute on Governance — baselgovernance.org/about/careers. Each vacancy is a linked PDF, so there's no HTML description to language-check. The rounded-3xl card class is what separates vacancy tiles from the annual-report PDF link.
    • These boards use UN-flavoured titles ("Information Management Officer", "ICT Specialist") that SOFTWARE_TITLE_RE alone drops, so INTL_TECH_RE widens the net for these sources only. Boards this small can afford the noise; missing a rare opening can't.
  • itjobs.ch is swept Switzerland-wide (no location param) — the board is small, ~210 jobs over 7 pages, and locking it to Basel returned only ~9. It 404s one page past the end instead of serving an empty list. Each item embeds its full description, so the DE/FR check runs in-process via isEnglishDescription rather than costing a page fetch per job. Use job_location.name for location — it's the English form; the bare location field is German.
• index.ts — orchestrator: loads existing IDs from results/jobs.csv, calls fetchJobs, calls isEnglishContent for each new job, appends survivors to CSV.
• recheck.ts — calls fetchJobs(..., { raw: true }) to bypass SOFTWARE_TITLE_RE, then lists every new job that would be filtered out and prints word-frequency suggestions.

Filter pipeline (applied in order)

1. Switzerland location guard (card HTML) — extracts job-search-card__location from each card; drops jobs where location doesn't contain "Switzerland". Prevents LinkedIn from returning global results when geoId is ignored on unauthenticated requests.
2. NON_ENGLISH_RE (title) — drops German gender markers, umlauts, /in suffix, French accents/markers. Runs inside fetchJobs.
3. JUNIOR_TITLE_RE (title) — drops junior/intern/trainee/werkstudent. Runs inside fetchJobs.
4. JAVA_TITLE_RE (title) — drops Java-titled roles. Runs inside fetchJobs.
5. BIO_DOMAIN_RE (title) — drops roles whose domain is biology/chemistry/the lab bench (bioinformatics, biostatistics, GMP/MSAT, genomics, pathology, drug discovery, bench Scientist titles). Filters on the role, not the employer — software/platform/data jobs at Roche, Novartis, Swiss TPH and sciCORE stay in scope. Runs inside fetchJobs.
6. SOFTWARE_TITLE_RE (title) — requires a relevant tech/role term. Skipped when raw: true. Runs inside fetchJobs. 6.5. GERMAN_TITLE_RE (title) — drops "(German-speaking)" / "deutschsprachig" titles without a description fetch. Runs inside fetchJobs.
7. isViableContent / isViableUrl (description page) — one fetch, two checks: (a) counts DE/FR indicator words, drops if ≥ 6; (b) requiresGerman() drops English postings that demand German above B1. Runs in index.ts only (not recheck.ts). Adds 350 ms delay per job. isEnglishContent / isEnglishUrl remain exported for recheck.ts and temp scripts.

requiresGerman(text) is deliberately more than a keyword match — Rafael is German B1 (TELC), so B1/"basic"/"a plus" is fine and B2+ is not. For each mention of German it takes the nearest qualifying marker, and a marker is ignored when another language name sits between it and the mention. Both rules come from real false results:

• "Infrastructure skills are a plus … Good knowledge of German" (Helvetia) — presence-based matching let an unrelated "a plus" 95 chars away cancel a real requirement.
• "Fluent in English; German and/or French advantageous" (albedis) — "Fluent" is nearer to "German" than "advantageous" is, but qualifies English.

Deduplication: job IDs are extracted from results/jobs.csv on startup; any ID already seen is skipped before content-checking.

SearchConfig

url overrides all filter params. Otherwise build from: keywords, geoId/location, workType, jobType, timePosted, seniority.

Known Swiss geoIds:

• Basel city: 103383283
• Basel Metropolitan Area: 90009885
• Basel-Country: 107117530
• Zürich city: 102436504
• Zürich Metropolitan Area: 107814425
• Zürich Area: 90009888

Use location: "City, Switzerland" (no geoId) when the geoId is unknown — LinkedIn resolves by name.

Auth warning: Do NOT send the li_at cookie in job search requests (/jobs/search/). With the cookie, LinkedIn serves the React SPA instead of server-rendered HTML, breaking the card parser entirely. The cookie is only useful for individual profile pages.

Searching any city / mode temporarily

Write a throwaway script in scripts/ (e.g. scripts/bern-temp.ts) — never touch config.ts unless the user explicitly asks to save the change. Delete temp scripts after the session unless the user asks to keep them.

Common patterns:

// City search (onsite + hybrid)
import { KEYWORDS } from "../config.ts";
import { fetchJobs } from "../fetch.ts";
import type { SearchConfig } from "../config.ts";

const config: SearchConfig = {
  label: "Bern", keywords: KEYWORDS, location: "Bern, Switzerland",
  workType: ["onsite", "hybrid"], timePosted: "month",
};
const jobs = await fetchJobs(config);
for (const j of jobs) console.log(j.title, j.company, j.link);

// Remote-only across all Switzerland
const config: SearchConfig = {
  label: "Switzerland Remote", keywords: KEYWORDS, location: "Switzerland",
  workType: ["remote"], timePosted: "month",
};

// Description-level keyword check (e.g. Ruby/Rails)
const RUBY_RE = /\bruby\b|\brails\b/i;
// fetch each job page, test RUBY_RE against the description text

Extra filters for temp scripts (import from ../fetch.ts):

• JAVA_TITLE_RE — drop Java roles
• JUNIOR_TITLE_RE — drop junior/intern
• isEnglishContent(id) — drop DE/FR description content
• Add your own inline RE for EMEA, .NET, etc.

Ranking jobs against the CV

Read cv/polo.md for the full profile. Key signals:

• Seniority: Senior / Staff / Principal / Lead / Architect — weight titles accordingly
• Core stack: Python · TypeScript · Ruby on Rails · React · Node.js
• Domain strengths: platform engineering · data pipelines · AI/LLM integrations · DevOps (Docker, Kubernetes, CI/CD, AWS)
• Background edges: fintech/CBDC (Moedax), civic tech (Tactical Tech / GFOSS), independent consulting (ExtraPolo, 40+ projects)
• Languages: English (full) · German B1 TELC certified · Spanish (full) — drop roles requiring German above B1; requiresGerman() does this automatically at fetch time
• Hard no: biological domains — drop bioinformatics, computational biology, biostatistics, lab/bench Scientist, GMP/MSAT, clinical/assay and drug-discovery-science roles; he has no life-science background. Software roles at pharma companies are still strong targets
• Hard no: Microsoft stack — drop .NET/C#, Azure-first, Windows/SCCM/Intune, SharePoint, Dynamics, Power Platform roles entirely; don't present them even as weak fits
• Location: based in Basel, open to Basel / Bern / Zürich; EU citizen, no permit needed

Output format

Always present jobs as a markdown table — never as a bullet list or prose: #, Title, Company, Canton, Why it fits, Link.

Canton is mandatory on every table, including single-city searches and the list of dropped/rejected jobs (there Why dropped replaces Why it fits). Derive it from the actual location on the posting, not from the search label — recruiters and multi-site companies often post under a different area than the job sits in. Use the two-letter code: BS, BL, ZH, BE, ZG, LU, VD, GE, TI, AG, SG, TG. For remote roles write Remote (add scope if known, e.g. Remote (EU)).

Links use just the job ID as anchor text: [4192954199](https://www.linkedin.com/jobs/view/4192954199/)

Workflow: "find jobs in X city / remote / custom search"

1. Write a temp script in scripts/ with the right SearchConfig (city, workType, custom keywords).
2. Apply extra inline filters as needed: EMEA, .NET, description-level keyword check.
3. Run isEnglishContent per job to drop DE/FR content.
4. Rank survivors against cv/polo.md, present as a table.
5. Delete temp scripts after the session unless asked to keep them.

LinkedIn session token

.env contains LI_AT — the LinkedIn session cookie (li_at value). Use it to fetch authenticated LinkedIn pages via curl:

curl -s "https://www.linkedin.com/in/<slug>" \
  -H "Cookie: li_at=$(grep LI_AT .env | cut -d= -f2-)" \
  -H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36" \
  --compressed -o /tmp/profile.html

What works: Full HTML pages for profiles that don't 999-block (varies by profile). Extract data with Python regex on the HTML.

What doesn't: LinkedIn Voyager API returns 401/403 (CSRF issues). ch.linkedin.com slugs sometimes work when www.linkedin.com returns HTTP 999. Public profiles without login redirect to a 1530-byte JS stub — no useful data.

Tip: Profile data is embedded as escaped JSON in the HTML. Use html.unescape() + regex for "headline", "locationName", defaultLocalizedName fields.

Workflow: "check if new keywords should be added"

1. Run bun recheck.
2. Identify false negatives — real software roles that got dropped.
3. Ignore generic frequency suggestions (engineer, development, senior).
4. Propose specific additions to SOFTWARE_TITLE_RE in fetch.ts or words to NON_ENGLISH_RE.