| name | bulk-optimize |
| description | Bulk skill optimization for external PR contributions. Greps for "auto-generated" markers to skip generated files, validates Python/JS syntax with ast.parse and node --check, checks git log for recent migrations, runs tessl skill review, and generates PR templates with before/after scores. Use when improving multiple skills in external repositories, preparing bulk PRs, contributing skill improvements, batch editing skills, or mass updating open source skills.
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Bulk Optimize
Improve external SKILL.md files for PR contributions using tessl skill review plus safety checks that prevent rejected PRs. Respects maintainers by detecting auto-generated files, preserving domain expertise, and suggesting appropriate PR scope.
For External PR Contributions
Adds safety checks for contributing to other people's repositories. See TEMPLATES.md for lessons from past PR rejections.
Workflow
Phase 1: Safety Checks (CRITICAL)
Run before making changes to prevent rejected PRs:
grep -i "auto-generated\|generated by\|DO NOT EDIT\|generator:" <skill-path>/SKILL.md
git log --oneline -10 --all -- <skill-directory>/ | grep -i "migrate\|rename\|move"
find . -name "SKILL.md" -type f | head -5 | xargs head -20
If auto-generated detected: STOP - changes must go to generator source
If recent migration found: WARN - may cause merge conflicts
Note domain patterns: Preserve expert framing and terminology in Phase 4
Phase 2: Baseline Evaluation
Run review for each skill:
tessl skill review <skill-path>/SKILL.md
Parse output to extract:
- Overall score
- Validation issues
- Description/content dimension scores
- Judge suggestions
If improving multiple skills:
- Track baseline scores for all
- Identify which need improvement most
- Consider PR scope (see Phase 7)
Phase 3: Discover Skill Bundle
Read SKILL.md and list files in its directory. Bundle = SKILL.md + sibling files + referenced files. Use for progressive disclosure improvements.
Use bundle context for recommendations.
Phase 4: Generate Recommendations (Preserve Domain Expertise)
Review recommendations to preserve valuable domain knowledge. Grep for specialized terminology (CRO, funnel, A/B test, etc.).
KEEP: Expert framing with domain concepts ("CRO expert who understands funnel optimization, conversion psychology...")
REMOVE: Generic expert statements ("You are an expert at helping users...")
For each issue: what to change, why (dimension + score), before/after, impact, domain check.
Phase 5: Validate Recommendations
import ast
ast.parse(code_snippet)
gh pr create --help | grep -q "\-\-flag" || echo "Invalid"
[[ -f "$SKILL_DIR/$FILE" ]] || echo "Missing file"
Phase 6: Present Recommendations
Show recommendations with:
- Current state (score)
- Issue explanation
- Recommended change
- Impact
- Domain preservation note
Get approval per skill or in batch (user choice).
Phase 7: PR Scope Assessment
Multiple skills (15+): Recommend one-skill-per-PR for easier review. Start with 2-3 highest-impact, get feedback, iterate.
High-scoring skills (90%+): Open issue first before unsolicited PR. Risk: maintainer may not want cosmetic changes.
Phase 8: Apply Changes
Apply approved changes to approved skills only.
Phase 9: Verify Improvements
tessl skill review <skill-path>/SKILL.md
Show before/after scores.
Phase 10: Final Accuracy Review
Re-run validation from Phase 5 on updated SKILL.md. Check:
- ✓ Code syntax valid
- ✓ Command flags correct
- ✓ File references exist
- ✓ Third-person voice
- ✓ "Use when..." clause present
Fix issues, then re-run tessl skill review.
Phase 11: PR Guidance
Use commit message format, PR description template, and best practices from TEMPLATES.md. Display ready-to-create PR info for user confirmation.
Notes
- Uses
tessl skill review plus PR-specific safety checks
- For external PR work on repos you don't maintain
- For personal skill improvement, use
skill-optimizer instead
