notion-linkedin-resume-pipeline

name

notion-linkedin-resume-pipeline

description

Configure and run a reusable end-to-end job-hunt pipeline: collect jobs from LinkedIn with user-defined filters, write rows/pages into a Notion database, generate tailored ATS resumes from a resume knowledge base, and update status/note fields. Use when a user asks to automate recurring job search + Notion tracking + resume generation workflows, including onboarding questions and per-user configuration.

Notion LinkedIn Resume Pipeline

Build a reusable workflow that can be configured per user and then run daily/weekly.

Quick workflow

1. Collect user configuration once.
2. Validate data sources (Notion DB, job source reachability, resume library).
3. Save config to a profile file.
4. Run fixed script once in dry-run/limited mode.
5. Schedule recurring execution via openclaw cron using the fixed script.
6. Post completion summary (counts + failures + notes), not attachments unless requested.

Fixed script (must use)

Primary script:

• scripts/run_pipeline.py

Usage:

• python3 scripts/run_pipeline.py --env ./.secrets/notion.env --output-dir ./generated_resumes --max-accept 12

If script execution fails, debug from error reason and rerun in the same turn.

Filename safety + retry rules (mandatory)

1. Never write resume files with placeholder tokens (e.g., Company, Position).
2. Validate company and position before generation; empty/placeholder values are immediate failures.
3. On placeholder/metadata failure, retry extraction/regeneration up to 5 attempts.
4. If still failing after 5 attempts, write failure reason into Notion note and include it in the daily report.

Step 1) Collect onboarding config (ask these in order)

Use this exact checklist during setup.

A. Destination and state

• Notion database/page link
• Required columns and types (minimum: Name, Status, URL, position, note)
• Status workflow values (example: Not started -> resume)
• Whether to create child page content with full JD text

B. Job search policy

• Sources (LinkedIn only / LinkedIn+Seek etc.)
• Time window (example: last 24h)
• Location policy (country + city priority)
• Target role families (example: Software Engineer, Data Analyst, Data Scientist, AI Engineer)
• Seniority policy (graduate/junior)
• Exclusion policy (citizenship/PR-only, years of experience thresholds, degree restrictions)
• Tech-stack fit threshold rule (example: reject when mismatch >= 80%)

C. Resume generation policy

• Resume knowledge base location (files/folders)
• Mandatory sections and section order
• Formatting rules (font, sizes, separators, bullet/dash style, line layout)
• Naming format for generated files (example: Company - Position Resume.docx)
• Delivery policy (attach files vs summary-only)

D. Automation and reporting

• Schedule (cron + timezone)
• Reporting destination (channel/user)
• Required daily summary fields:
  • searched count
  • filtered-in count
  • inserted count
  • resumes generated count
  • status updated count
  • failures with reasons

Step 2) Validate prerequisites

Before first run:

• Verify Notion token and DB access.
• Verify required Notion columns; create missing note rich_text column.
• Verify job source access limitations (captcha/403) and define fallback behavior.
• Verify resume source files are readable.

If any prerequisite fails, stop and return a setup report with exact fixes.

Step 3) Persist user profile config

Store config in a reusable profile file (JSON or markdown) under workspace, e.g.:

• profiles/job-pipeline/<user>.json

Include:

• source filters
• exclusion rules
• resume formatting template
• Notion field mapping
• schedule/report destination

Step 4) Execution contract (per run)

Run in this order:

1. Search jobs by time window.
2. Apply all hard filters.
3. Insert accepted jobs into Notion.
4. Traverse Notion rows where Status=Not started.
5. Generate tailored resume per row.
6. If success, set Status=resume; write remarks to note.
7. Post summary report.

Always write operational notes to note when something is unusual (missing company values, restricted eligibility, extraction issues, anti-bot block, JD ambiguity).

Step 5) Resume tailoring rules

For each role:

• Map JD keywords to candidate evidence from resume knowledge base.
• Rewrite Professional Profile to combine:
  • role requirements
  • company value/culture signals (from official pages when available)
  • candidate achievements
• Keep ATS-safe language and measurable outcomes.
• Keep concise (1-2 pages unless user overrides).

Step 6) Scheduling

Use openclaw cron add with:

• timezone set explicitly
• isolated session preferred for repeatability
• announce summary only unless user asks for attachments

If schedule changes, edit job instead of creating duplicates.

References

• Onboarding questionnaire template: references/onboarding-template.md
• Config schema template: references/config-schema.json
• Daily run report template: references/report-template.md