How Realtime Functionality and Updates Are Handled in ai-job-search

The ai-job-search repository implements realtime job searching through on-demand CLI skill execution that fetches live data via HTTP requests, while framework updates are managed through explicit version metadata and Python utilities that track upstream changes.

This repository does not run a continuously-running server. Instead, all realtime behavior is performed on-demand when users invoke CLI skills or helper scripts, with framework modifications tracked through explicit version markers and sync utilities.

Real-Time Job Portal Queries

Live Search Execution

When a user requests job listings, the repository executes live searches by sending fresh HTTP requests to public job-board APIs or scraping current HTML pages. The TypeScript CLI files under .agents/skills/*/cli/src/ use fetch, axios, or curl via Bash to retrieve data at execution time. No background polling or caching layer is performed.

For example, the Jobindex skill executes searches through its CLI entry point at .agents/skills/jobindex-search/cli/src/cli.ts. According to the accompanying .agents/skills/jobindex-search/SKILL.md documentation, this skill searches "live Danish job listings" with no authentication required, confirming that each invocation triggers a real-time network call.

Live Detail Fetching

After retrieving search results, users can request detailed information for specific job postings using the detail <id> command. This functionality performs a second HTTP request to the job-board's live endpoint to return the full posting, deadline, and application link. The detail implementation resides in the same CLI command files that handle the initial search, ensuring all data reflects the current state of the job portal.

Continuous Integration Constraints

The GitHub Actions workflow at .github/workflows/ci.yml deliberately excludes live portal testing. The configuration file contains explicit comments such as "Deliberately NOT here: live smoke tests of the job‑portal CLIs" and executes only static type-checks and fixture tests. This design prevents CI pipelines from hitting external rate limits while maintaining code quality.

Example: Running a Real-Time Search

To execute a live search for Python jobs posted in the last seven days:

bun run .agents/skills/jobindex-search/cli/src/cli.ts search \
  --query python \
  --jobage 7 \
  --sort date \
  --format table

This command contacts jobindex.dk at execution time, returning the current 20 results (or more if --limit is specified) without any cached data.

Framework Versioning and Update Management

Enforcing Version Bumps with check_framework_version.py

The repository versions its methodology files using a framework_version front-matter field in markdown files. The script tools/check_framework_version.py ensures that any edited framework file has its version marker incremented. If the version is out-of-date, the CI pipeline fails, preventing unversioned changes from merging.

Previewing Upstream Changes with check_upstream_updates.py

To synchronize with upstream changes, the repository provides tools/check_upstream_updates.py. This utility calls git fetch on the upstream remote, computes a diff between origin/master and the local branch, and prints a list of touched files with their new version markers. Users can preview changes before merging:

python3 tools/check_upstream_updates.py

When accepting changes, users merge via standard Git workflow (git merge upstream/master). The version bump in each updated file signals that framework behavior—such as new scoring rules or CLI flag defaults—may have changed.

Optional File System Monitoring

The repository includes a Watchman hook at .git/hooks/fsmonitor-watchman.sample that optimizes local Git performance by reporting file changes. This optional integration calls watchman query to obtain a clock token and changed path list, speeding up Git operations but remaining unrelated to job-portal queries.

Summary

• On-demand execution: Realtime job searches occur only when CLI skills are invoked, with no continuous server or background polling.
• Live HTTP requests: Skills under .agents/skills/*/cli/src/ use fetch, axios, or curl to retrieve current data directly from job portals.
• CI isolation: The GitHub Actions workflow deliberately skips live network calls to avoid rate limiting and external dependencies in testing.
• Versioned updates: Framework changes use framework_version front-matter tracked by tools/check_framework_version.py and tools/check_upstream_updates.py.
• Fork synchronization: The check_upstream_updates.py script previews upstream changes before merging, ensuring controlled framework updates.

Frequently Asked Questions

Does ai-job-search maintain a background service for realtime updates?

No. The repository does not run a continuously-running server or daemon. All realtime functionality is performed on-demand when a user invokes a specific CLI skill, which then executes HTTP requests to fetch current job data.

How does the repository prevent CI pipelines from hitting job portal rate limits?

The .github/workflows/ci.yml configuration explicitly excludes live smoke tests. Comments in the workflow indicate that live portal CLI tests are "Deliberately NOT here," ensuring that automated testing performs only static analysis and fixture-based validation without external network calls.

What triggers a framework version check in the methodology files?

Any modification to a framework methodology file (marked with framework_version front-matter) triggers the tools/check_framework_version.py validator. The CI pipeline runs this check to ensure the version marker is incremented, failing the build if an edited file lacks a proper version bump.

Can I preview upstream changes before merging them into my fork?

Yes. Running python3 tools/check_upstream_updates.py fetches the upstream remote and displays exactly which methodology files have changed, along with their new version markers. This allows you to review changes before executing git merge upstream/master.

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