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jobwatch
Automate job board monitoring and application tracking via the jobwatch MCP server.
Free
jobwatch
Example session with this skill installed
Check my watched job boards and show me what's new today. Queue the best two, and tell me if I know anyone at those companies.
- Read your context and instructions
- Compiled the jobwatch
Example session; the companies are samples.
I ran fetch_jobs (42 boards checked, 3,118 open roles, 27 new), then get_digest for the new matches. Here are the top five:
| # | Company | Role | Fit | Why | Check first |
|---|---|---|---|---|---|
| 1 | Globex | Staff Platform Engineer | 86 | Owns the job queue rewrite you've done before | Remote, US |
| 2 | Initech | Senior Security Automation Engineer | 81 | SOAR playbooks and Python, both on your resume | Posted pay $190-230K |
| 3 | Acme | Principal Engineer, AI Agents | 77 | Agent tooling and MCP | Hybrid, 2 days |
| 4 | Umbrella | Backend Engineer | 64 | Good stack match | Below your level |
| 5 | Hooli | ML Platform Engineer | 61 | Needs Kubernetes, which you don't list | Onsite |
I queued
Globex and
Initech with mark_job. list_queued_jobs shows you know one person at Initech (a former teammate), so asking them for a referral first is worth it. Nobody you know is at Globex.
Next steps
- Say "tailor my resume for Globex" and I'll read the full posting with
get_job. - I won't submit anything: once you apply, tell me and I'll mark it
appliedand save what you sent.
Connects securely to your tools. The creator never sees your data.
About this skill
Managing a high-volume job search manually leads to missed deadlines, lost application versions, and stale leads. This skill integrates the jobwatch MCP server into your agent, automating the monitoring of company job boards and centralizing every stage of the application lifecycle.
What it does
- Monitor boards watches Greenhouse, Lever, Ashby, and Workday boards for new postings.
- Rank matches generates a daily digest of new roles filtered by user relevance.
- Track status maintains a local record of applications from screening through to offer.
- Store packages saves the specific resume and cover letter versions used for every submission.
- Prep interviews generates study sheets by mapping job requirements against your stored stories.
- Analyze gaps identifies skills frequently requested in target roles that are missing from your profile.
How it works
- Watchlist setup uses
find_boardandadd_boardto track specific companies or careers pages. - Daily sync runs
fetch_jobsandimport_job_alertsto aggregate new leads from boards and email alerts. - Queue management uses
mark_jobto move leads into a queued state for review and tailoring. - Lifecycle tracking updates application stages based on user input or confirmed email status updates.
Frameworks & tools
This skill requires the jobwatch Python package with MCP support. It interfaces with local jobwatch.yaml configurations and stores application data in a local filesystem for privacy.
Why this beats prompting it yourself
Generic agents cannot monitor live job boards or maintain a persistent, local database of application history. This skill provides the specific toolset to read board-specific schemas and manage state across weeks of interviewing.
Use cases
- Daily sourcing finding and ranking new openings at a curated list of 50 target companies.
- Interview preparation generating a tailored brief based on the exact resume version submitted.
- Follow-up tracking identifying applications that have gone quiet or require a check-in.
- Portfolio management keeping a local, private record of offer details and recruiter contacts.
Known limitations
Requires local installation of jobwatch via pipx or pip. It cannot automatically submit applications and requires the user to perform the final submission.
Requires local jobwatch MCP server installation. Does not automate the actual submission of applications. Email integration requires a separate mail connector setup.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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