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Frequently Asked Questions
Common questions from the community, answered in one place. For setup details see docs/SETUP.md. For anything not covered here, ask in Discord or open a GitHub Discussion.
1. Skills aren't loading on Windows — symlink error on install
Windows does not create symlinks by default, so Git checks out the CLI skill entrypoints (.claude/skills/, .opencode/skills/, etc.) as plain pointer files instead of real symlinks. The installer and updater both detect this automatically: run node update-system.mjs apply (or npx @santifer/career-ops init on a fresh install) and the materializeSkillEntrypoints step will replace the pointer files with the full canonical skill content. No manual mklink or Developer Mode changes are needed.
2. What is the difference between scan and scan:full?
npm run scan is the standard portal scanner — it reads the companies you have configured in portals.yml, hits their ATS APIs (Greenhouse, Ashby, Lever) directly, and consumes zero LLM tokens. Use it for your regular daily or weekly discovery run. npm run scan:full inverts the direction: instead of scanning your curated list, it walks public ATS company directories and surfaces any fresh postings that match your title_filter / location_filter, so you catch roles from companies you haven't manually added to portals.yml. Run scan:full when you want broader discovery beyond your tracked list.
3. How do I avoid hitting token or rate limits during a batch run?
Pass --limit <N> to batch-runner.sh to cap the number of offers processed in a single run (e.g. ./batch/batch-runner.sh --limit 5) — this lets you inspect output quality before committing to a larger run. If a run is interrupted mid-way by a rate limit or network error, do not restart from scratch; use ./batch/batch-runner.sh --resume-paused to skip already-completed jobs and pick up where you left off, avoiding wasted tokens on work that finished successfully.
4. Can I run career-ops on a cheaper or local model?
Yes — career-ops is fully AI-agnostic and works with any AI coding CLI or standalone script. See docs/RUNNING_ON_A_BUDGET.md for a full guide covering OpenCode, Qwen CLI, DeepSeek, OpenRouter, Ollama, and other local or low-cost providers, along with recommended model sizes and token-saving best practices.