docs: cover the digest layer and scheduled jobs

Rewrite the README around the current pipeline: the twice-daily Telegram
digest, the sciCORE watcher, Telegram setup, and the two-stage filter
pipeline.

CLAUDE.md gains the bun daily commands, the daily/profile/telegram
architecture notes, and a scheduled-automations section covering both
launchd agents. Records that fetch.ts gates what reaches the CSV while
profile.ts gates what reaches the phone.
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@@ -8,6 +8,10 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
|---|---|
| `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 |
| `bun daily` | fetch, then push new profile-matching jobs to Telegram |
| `bun daily --dry-run` | same, but print the message instead of sending |
| `bun daily --resend` | skip fetching, re-send today's jobs from the CSV (`--date=YYYY-MM-DD` to pick a day) |
| `bun run telegram.ts --setup` | print the chat ID for `.env` after messaging the bot |
Temp scripts: `bun run scripts/<name>-temp.ts` — never edit `config.ts` for one-off searches.
@@ -19,7 +23,12 @@ 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
daily.ts # digest: fetch → match against profile.ts → send to Telegram
profile.ts # title-level scoring; decides what's worth a notification
telegram.ts # Telegram delivery, chunking, --setup chat-ID discovery
scripts/ # one-off search scripts; import from ../config.ts and ../fetch.ts
scripts/scicore-watch.sh # daily launchd watch on sciCORE's open-positions page
results/sent.txt # links already pushed to Telegram — never sent twice
cv/polo.md # Rafael's profile — use for ranking jobs
cv/ # CV files (html, pdf, odt)
results/jobs.csv # output — one row per job
@@ -43,6 +52,9 @@ plans/ # LinkedIn post drafts
- **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.
- **`daily.ts`** — the notification layer on top of `index.ts`. Snapshots the CSV's links, shells out to `bun fetch`, then diffs to find what's new. Survivors are filtered through `matchesProfile` and grouped by area (Basel / Remote / Zürich / Bern) so the message scans on a phone. `results/sent.txt` is written **only after a successful send**, so a Telegram failure retries next run instead of silently losing jobs. A non-zero exit from `bun fetch` sends a failure notice rather than failing quietly.
- **`profile.ts`** — `matchesProfile(title, company, minScore = 4)`. Hard rejects run first (Microsoft stack, Java/C++/SAP, life-science, non-software functions, blocked companies Jobgether and ALLPS), then `SIGNALS` scores stack and seniority terms from `cv/polo.md`. This is a **second, stricter gate than the fetch filters**: `fetch.ts` decides what lands in the CSV, `profile.ts` decides what's worth a phone buzz. Widen `SOFTWARE_TITLE_RE` to catch more in the CSV; tune `SIGNALS`/`minScore` to change what gets sent.
- **`telegram.ts`** — reads `.env` directly (no dotenv dep). Accepts `TELEGRAM_BOT` or `TELEGRAM_TOKEN` for the token. Splits at 3900 chars on line boundaries (Telegram hard-caps at 4096) and sleeps 400 ms between parts to stay under the rate limit. Messages are HTML — run titles/companies through `escapeHtml`.
### Filter pipeline (applied in order)
@@ -146,9 +158,32 @@ Links use just the job ID as anchor text: `[4192954199](https://www.linkedin.com
4. Rank survivors against `cv/polo.md`, present as a table.
5. Delete temp scripts after the session unless asked to keep them.
## Scheduled automations
Both run as **launchd agents** — this machine has no cron at all, so don't reach for `crontab`.
| plist (`~/Library/LaunchAgents/`) | when | runs |
|---|---|---|
| `com.rafapolo.linkme-daily` | 08:00 + 18:00 | `bun run daily.ts` → `results/daily.log` |
| `ch.polo.scicore-watch` | 08:47 | `scripts/scicore-watch.sh` → `results/.scicore-watch/watch.log` |
If the Mac is asleep at the scheduled time, launchd fires the job on wake rather than skipping the day. `launchctl list | grep -E 'linkme|scicore'` to check they're loaded; `launchctl unload <plist>` to stop one.
**`scripts/scicore-watch.sh`** watches https://scicore.unibas.ch/about-scicore/open-positions/ for a software engineering role Rafael is waiting on. It extracts the "Join the team!" block (keeping each posting's `<a href>` so the alert is tappable), diffs it against `results/.scicore-watch/snapshot.txt`, and notifies **only when a newly added line matches `$WANTED` ("software")**. Every other change still updates the snapshot silently — that's what keeps the eventual real alert clean instead of tangled with months of sysadmin churn. Three consecutive fetch failures alert, so a broken watcher can't look like "no news".
Test the alert path without waiting for the page to change:
```bash
SCICORE_URL="file://$PWD/fixture.html" bash scripts/scicore-watch.sh
```
The whole extractor is a `python3 -c` program inside shell single quotes, so **it must not contain a literal apostrophe** — that's why the `<a>` quote class is built with `chr(39)` instead of written inline.
## LinkedIn session token
`.env` contains `LI_AT` — the LinkedIn session cookie (`li_at` value). Use it to fetch authenticated LinkedIn pages via curl:
`.env` holds `LI_AT` (LinkedIn session cookie), plus `TELEGRAM_BOT` and `TELEGRAM_CHAT_ID` for the digest. It is gitignored.
`LI_AT` is the `li_at` cookie value. Use it to fetch authenticated LinkedIn pages via curl:
```bash
curl -s "https://www.linkedin.com/in/<slug>" \
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# linkme
Scrapes LinkedIn job listings into a local CSV. Run it daily, delete rows you've applied to.
A personal job-hunting pipeline for the Swiss market. It scrapes LinkedIn (plus a handful of Swiss boards), filters out everything that doesn't fit the profile in `cv/polo.md`, appends what survives to a CSV, and pushes the good ones to Telegram twice a day.
## Usage
Two things run on their own once installed:
| automation | when | what it does |
|---|---|---|
| **daily digest** | 08:00 + 18:00 | fetch every search, push new profile-matching jobs to Telegram |
| **sciCORE watch** | 08:47 | alert if sciCORE's open-positions page lists a *software* role |
## Quick start
```bash
bun fetch # scrape and append new jobs to results/jobs.csv
bun recheck # show jobs currently filtered out + keyword suggestions
bun fetch # scrape all searches, append new jobs to results/jobs.csv
bun daily # fetch, then Telegram the new jobs that match the profile
bun recheck # show what the filters are currently dropping + keyword suggestions
```
No setup needed. Results are appended to `results/jobs.csv` — reruns are safe, already-seen jobs are skipped by ID.
`bun fetch` needs no setup — reruns are safe, already-seen jobs are skipped by ID. Telegram needs the two-line setup below.
## Telegram setup
```bash
# 1. Message @BotFather → /newbot → copy the token into .env
echo 'TELEGRAM_BOT=<token>' >> .env
# 2. Send your bot any message ("hi"), then discover your chat ID
bun run telegram.ts --setup # prints TELEGRAM_CHAT_ID=... — paste it into .env
```
Then `bun daily --dry-run` prints the digest instead of sending it, and `bun daily --resend` re-sends today's jobs from the CSV without re-fetching.
`.env` also holds `LI_AT`, a LinkedIn session cookie used only for fetching individual *profile* pages. Never send it with a job search — with the cookie LinkedIn serves a React SPA instead of server-rendered HTML and the card parser gets nothing. `.env` is gitignored.
## Structure
```
config.ts # search keywords and areas
fetch.ts # scraper, HTML parser, filters
fetch-other.ts # extra sources (datacareer.ch, stellen-basel.ch)
index.ts # orchestrator: runs searches, writes CSV
recheck.ts # raw-mode fetch, lists filtered-out jobs
scripts/ # one-off search scripts (temp, not in config.ts)
cv/ # polo.md (profile) + CV files
results/ # jobs.csv output
jobs/ # notes on specific job leads
plans/ # LinkedIn post drafts
config.ts # keyword families, search areas, the sweep() generator
fetch.ts # LinkedIn scraper, HTML parser, all title/content filters
fetch-other.ts # extra sources: itjobs.ch, job-room.ch, stellen-basel.ch,
# datacareer.ch (403, currently dead), Basel intl orgs
index.ts # orchestrator: run searches → dedupe → content-check → CSV
recheck.ts # raw-mode fetch: lists what the filters dropped
daily.ts # digest: fetch, match against the profile, send to Telegram
profile.ts # title-level scoring — decides what's worth a notification
telegram.ts # Telegram delivery + --setup chat-ID discovery
scripts/ # one-off searches (*-temp.ts) and scicore-watch.sh
cv/polo.md # the profile everything is ranked against
results/jobs.csv # output, one row per job
results/sent.txt # links already pushed — never sent twice
```
## How a job gets through
Two stages. Cheap title filters first, then one page fetch per survivor.
**Title filters** (inside `fetchJobs`, no network cost):
1. **Switzerland guard** — the card's location must say Switzerland. LinkedIn ignores `geoId` on unauthenticated requests and will happily return global results.
2. `NON_ENGLISH_RE` — German gender markers (`m/w/d`, `/in`), umlauts, French `H/F` and accents.
3. `JUNIOR_TITLE_RE` — junior, intern, trainee, werkstudent, entry-level.
4. `JAVA_TITLE_RE` — Java-titled roles.
5. `BIO_DOMAIN_RE` — bioinformatics, biostatistics, genomics, GMP/MSAT, bench-scientist titles. Filters on the **role, not the employer**: software and data jobs at Roche, Novartis or Swiss TPH stay in.
6. `SOFTWARE_TITLE_RE` — requires a real tech/role term. Skipped in `raw` mode, which is what `bun recheck` uses.
7. `GERMAN_TITLE_RE` — "(German-speaking)", "deutschsprachig".
**Content check** (`index.ts` only, one fetch + 350 ms per job): `isViableContent` counts German/French indicator words and drops at ≥ 6, then `requiresGerman()` drops English postings demanding German above B1.
That last one is deliberately more than a keyword match. For each mention of German it takes the *nearest* qualifying marker, and ignores a marker when another language name sits between it and the mention — both rules came from real false results, like *"Fluent in English; German and/or French advantageous"*, where "Fluent" sits closer to "German" than "advantageous" does but qualifies English.
**Profile match** (`profile.ts`, digest only) scores the title against the CV's stack and seniority signals, needing 4+ points to notify. Hard rejects encode standing decisions: Microsoft stack, Java/C++/SAP, life-science domains, non-software functions, and the blocked companies Jobgether (an aggregator, not an employer) and ALLPS (postings require German despite passing the English filter).
Jobs are deduped globally by ID against `results/jobs.csv` on startup, so nothing is ever fetched or sent twice.
## Output
`results/jobs.csv` — one row per job:
`results/jobs.csv` — `date_found`, `posted_at`, `search`, `title`, `company`, `link`, `source`. Open it in any spreadsheet and delete rows as you apply or dismiss.
| column | description |
|---|---|
| `date_found` | date you ran the fetch |
| `posted_at` | date the job was posted |
| `search` | which search config matched it |
| `title` | job title |
| `company` | hiring company |
| `link` | canonical job URL |
| `source` | site the job came from |
## Configuring searches
Open in any spreadsheet app. Delete rows as you apply or dismiss.
## How it works
- **Paginated scraping** — fetches up to 6 pages per search (150 jobs) with a 400 ms delay between pages
- **Card-boundary-safe parsing** — each job card is isolated before extracting fields
- **Language filter** — drops German (`m/w/d`, umlauts, gender markers) and French (`H/F`, accents) titles
- **Software-role filter** — requires a relevant term in the title (software, developer, data, AI, backend, frontend, devops, platform, architect, tech lead, typescript, python, rails, node.js, ML, cloud, security, SRE, etc.)
- **Seniority filter** — drops junior, intern, trainee, apprentice, werkstudent, entry-level
- **Global deduplication** — IDs indexed from existing CSV on startup; already-seen jobs are never re-added
- **30-day recency** — only jobs posted in the last month
## recheck
`bun recheck` fetches all searches in raw mode (bypassing the software-role filter) and lists every job that would be filtered out — useful for spotting false negatives. Also prints a word-frequency table of filtered titles to help decide what to add to `SOFTWARE_TITLE_RE`.
## Temporary searches
Write a throwaway script in `scripts/` instead of editing `config.ts`:
```bash
bun run scripts/bern-temp.ts
```
Scripts in `scripts/` import from `../config.ts` and `../fetch.ts`.
## Configure searches
Edit `config.ts`:
`config.ts` holds four keyword families as separate OR-strings — `KEYWORDS`, `PLATFORM_KEYWORDS`, `RESEARCH_KEYWORDS`, `FIELD_KEYWORDS`. They're kept apart on purpose: LinkedIn ranks a focused query far better than one 50-term disjunction. `sweep()` generates one search per area per family (Research skips Bern; Platform and Field add a Switzerland-wide remote pass).
```ts
export const KEYWORDS = "Software Engineer OR Data Engineer OR ...";
export const searches: SearchConfig[] = [
{
label: "Basel (city)",
keywords: KEYWORDS,
geoId: "103383283",
location: "Basel",
workType: ["onsite", "hybrid"],
timePosted: "month",
},
];
```
`SearchConfig` also takes `jobType`, `seniority`, and `location` (use `"City, Switzerland"` when the geoId is unknown — LinkedIn resolves by name). A `url:` field overrides all filter params, so you can paste a LinkedIn search URL directly.
Known Swiss geoIds:
- `103383283` — Basel (city)
- `90009885` — Basel Metropolitan Area
- `107117530` — Basel-Country
- `102436504` — Zürich (city)
- `107814425` — Zürich Metropolitan Area
- `90009888` — Zürich Area
You can also paste any LinkedIn search URL directly as `url:` instead of building from filters.
| area | geoId |
|---|---|
| Basel (city) | `103383283` |
| Basel Metropolitan Area | `90009885` |
| Basel-Country | `107117530` |
| Zürich (city) | `102436504` |
| Zürich Metropolitan Area | `107814425` |
| Zürich Area | `90009888` |
`SearchConfig` also supports `jobType` (full-time, part-time, contract, temporary, internship) and `seniority` (internship, entry, associate, mid-senior, director, executive).
## One-off searches
Don't edit `config.ts` for a single search — write a throwaway in `scripts/`:
```ts
import { KEYWORDS } from "../config.ts";
import { fetchJobs } from "../fetch.ts";
const jobs = await fetchJobs({
label: "Luzern", keywords: KEYWORDS,
location: "Luzern, Switzerland",
workType: ["onsite", "hybrid"], timePosted: "month",
});
for (const j of jobs) console.log(j.title, j.company, j.link);
```
```bash
bun run scripts/luzern-temp.ts
```
`*-temp.ts` scripts are disposable — delete them when the search is done.
## Scheduling
Both automations are launchd agents, not cron — this machine has no cron at all.
```bash
launchctl list | grep -E 'linkme|scicore' # are they loaded?
launchctl unload ~/Library/LaunchAgents/com.rafapolo.linkme-daily.plist # stop the digest
launchctl unload ~/Library/LaunchAgents/ch.polo.scicore-watch.plist # stop the watcher
```
If the Mac is asleep at the scheduled time, launchd runs the job once it wakes rather than skipping the day.
Logs: `results/daily.log` for the digest, `results/.scicore-watch/watch.log` for the watcher. The watcher logs every run — `no change`, `change ignored`, or the diff it sent — so silence on your phone can always be told apart from a broken script. Test its alert path without waiting for the real page to change:
```bash
SCICORE_URL="file://$PWD/fixture.html" bash scripts/scicore-watch.sh
```
## recheck
`bun recheck` re-runs every search with `SOFTWARE_TITLE_RE` bypassed and lists each job the filters would drop, plus a word-frequency table of those titles. Use it to spot false negatives; ignore the generic suggestions (`engineer`, `development`, `senior`) and look for real role terms worth adding to the regex.