agentic/code/addons/skill-factory/skills/skill-packager/SKILL.md
Package skills into uploadable ZIP files for Claude. Use after skill-builder/skill-enhancer to create final upload package.
npx skillsauth add jmagly/aiwg skill-packagerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Single responsibility: Package completed skill directories into ZIP files ready for upload to Claude AI. (BP-4)
Before executing, VERIFY:
DO NOT package without validating skill structure.
ASK USER instead of guessing when:
NEVER package potentially sensitive content without review.
| Context Type | Included | Excluded | |--------------|----------|----------| | RELEVANT | Skill directory contents, package config | Other skills | | PERIPHERAL | Package size estimates | Source data | | DISTRACTOR | Build process details | Scraping history |
# Required structure check
test -f output/<skill-name>/SKILL.md || echo "ERROR: Missing SKILL.md"
test -d output/<skill-name>/references || echo "ERROR: Missing references/"
# Check SKILL.md is not empty
test -s output/<skill-name>/SKILL.md || echo "ERROR: SKILL.md is empty"
# Check for at least one reference
ls output/<skill-name>/references/*.md >/dev/null 2>&1 || echo "ERROR: No reference files"
# Scan for potential sensitive data
grep -rE "(api[_-]?key|password|secret|token|credential)" output/<skill-name>/ && \
echo "WARNING: Potential sensitive data found - review before packaging"
# Check for large files
find output/<skill-name>/ -size +10M -exec echo "WARNING: Large file: {}" \;
# Check for binary files
find output/<skill-name>/ -type f ! -name "*.md" ! -name "*.json" ! -name "*.txt" \
-exec file {} \; | grep -v "text" && echo "WARNING: Non-text files found"
# Estimate final size
du -sh output/<skill-name>/
# Count files
find output/<skill-name>/ -type f | wc -l
# List file types
find output/<skill-name>/ -type f -name "*.*" | sed 's/.*\.//' | sort | uniq -c
Option A: With skill-seekers
# Standard packaging
skill-seekers package output/<skill-name>/
# With upload (if API key set)
skill-seekers package output/<skill-name>/ --upload
Option B: Manual packaging
# Navigate to output directory
cd output/
# Create ZIP (exclude backups and temp files)
zip -r <skill-name>.zip <skill-name>/ \
-x "*.backup" \
-x "*.tmp" \
-x ".DS_Store" \
-x "__MACOSX/*"
# Verify ZIP contents
unzip -l <skill-name>.zip
# Check ZIP integrity
unzip -t output/<skill-name>.zip
# Verify required files are included
unzip -l output/<skill-name>.zip | grep "SKILL.md"
unzip -l output/<skill-name>.zip | grep "references/"
# Check size is reasonable
ls -lh output/<skill-name>.zip
On error:
Missing files → Run skill-builder firstZIP error → Check disk space, permissionsLarge size → Exclude unnecessary filesSensitive data → Clean files, re-packageState saved to: .aiwg/working/checkpoints/skill-packager/
checkpoints/skill-packager/
├── validation_results.json # Pre-package validation
├── security_scan.json # Security check results
├── package_manifest.json # Files included
└── package_log.txt # Packaging process log
Generate manifest for verification:
{
"skill_name": "myskill",
"packaged_at": "2025-01-15T10:30:00Z",
"files": [
{"path": "SKILL.md", "size": 15234, "hash": "abc123..."},
{"path": "references/index.md", "size": 2045, "hash": "def456..."},
{"path": "references/api.md", "size": 45678, "hash": "ghi789..."}
],
"total_files": 5,
"total_size": 62957,
"package_size": 18234
}
export ANTHROPIC_API_KEY=sk-ant-...
skill-seekers package output/<skill-name>/ --upload
output/<skill-name>.zip"Package and upload the myskill skill"
Default exclusions:
*.backup
*.tmp
*.log
.DS_Store
__MACOSX/
.git/
node_modules/
__pycache__/
*.pyc
.env
*.key
*.pem
| Platform | Max Size | Recommendation | |----------|----------|----------------| | Claude.ai | 50MB | Keep under 10MB | | API | Variable | Keep under 20MB |
If over limit:
{
"skill_dir": "output/myskill/",
"output_zip": "output/myskill.zip",
"options": {
"include_manifest": true,
"compress_level": 9,
"exclude_patterns": ["*.backup", "*.tmp"],
"security_check": true,
"auto_upload": false
}
}
| Issue | Diagnosis | Solution | |-------|-----------|----------| | ZIP too large | Large assets | Exclude or compress images | | Missing files | Validation failed | Run skill-builder first | | Upload failed | API error | Check API key, retry | | Corrupt ZIP | Disk issue | Check disk space, re-create |
data-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.