القائمة
Automated book maintenance. Runs health checks, prioritizes work, and systematically fixes issues. Use when you want Codex to autonomously improve the book.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | book-autopilot |
| description | Automated book maintenance. Runs health checks, prioritizes work, and systematically fixes issues. Use when you want Codex to autonomously improve the book. |
| allowed-tools | ["Read","Edit","Write","Bash","Grep","Glob","Task"] |
Autonomous book maintenance system. Modes:
check - Run health check, generate report (default)fix - Fix all issues systematically (CRITICAL → LOW)chapter <name> - Focus on single chapterimages - Generate missing section imagesparams - Audit and fix parameter issuescitations - Find and add missing citationsRun comprehensive health check:
python scripts/book-health-check.py
Read the report and summarize top priorities:
cat _build_temp/book-health-report.md | head -100
python scripts/book-health-check.py --json > _build_temp/health-issues.json
Read the JSON output and process issues in order:
CRITICAL - Must fix immediately
HIGH - Fix before next render
/verify-and-add-sources/generate-section-imagesMEDIUM - Batch fix
/replace-hardcoded-valuesLOW - Opportunistic
/peer-reviewpython scripts/book-health-check.py --quick
Focus on a single chapter:
python scripts/book-health-check.py --chapter <name>
Then apply all relevant fixes to that chapter:
/replace-hardcoded-values on it/peer-review on itGenerate missing section images:
npx tsx scripts/images/generate-section-images.ts --limit 5
Review generated images and regenerate any that need improvement.
Parameter audit and fix:
python scripts/find-unused-parameters.py
npx tsx scripts/audit-hardcoded-all.ts
python scripts/generate-everything-parameters-variables-calculations-references.py
Find claims without citations:
grep -rn "studies show\|research indicates\|according to" knowledge/ --include="*.qmd" | head -20
/verify-and-add-sources to find and add proper citations.For ongoing maintenance, run this sequence periodically:
python scripts/book-health-check.py - Find issuesAfter each fix session, update progress:
# Count remaining issues
python scripts/book-health-check.py --json | python -c "import json,sys; d=json.load(sys.stdin); print(f'Remaining: {d[\"total_issues\"]} issues')"
Critique book prose in the author's voice using patterns learned from his own git edit history (not a hand-written rubric). Use when asked to "voice-check", "punch up", "make this sound like me / like Vonnegut / like Cunk", or to review whether a passage is too pompous / cute / self-aware. Catches what the regex scanner (voice-check.py, ~1.4% of real edits) misses.
Review and improve QMD chapter writing quality by replacing boring/consultant text with Wishonia's deadpan alien voice, consolidating redundancy, and reducing word count. Use when asked to fix voice, make content funnier, remove jargon, or enforce the book's writing style.
Spawns parallel agents to review all paperback QMD files. Reads variable-resolved previews, flags judgment-required issues with REVIEW comments.
Check GitHub Actions workflow status, diagnose failures, fetch logs, and fix common build issues. Use when builds fail, deploys break, or you need to investigate CI/CD problems.
Critically analyze a calculated parameter for academic rigor. Checks methodology, identifies weaknesses, suggests improvements for economist audiences.
Systematic book curation pipeline. Evaluates every chapter on 8 dimensions, identifies overlaps, and produces a scored report with actionable recommendations.