vibeeval/harvest-adaptive
skills/harvest-adaptive/SKILL.md
Adaptive content summarization - auto-detect content type and produce relevant summary
$ install --global
skillsauthnpx skillsauth add vibeeval/vibecosystem harvest-adaptiveInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 16, 2026, 1:49 AM4.2s1 file scanned
SKILL.md
- name:
- harvest-adaptive
- description:
- Adaptive content summarization - auto-detect content type and produce relevant summary
- allowed-tools:
- [Bash, Read, Write, WebFetch, WebSearch]
- keywords:
- [digest, summary, evaluate, library, tool, article, adaptive, overview]
Harvest Adaptive (Digest)
Automatically detect content type and produce the most useful summary. A blog post gets key takeaways. A library gets feature evaluation. Documentation gets structure overview. API reference gets endpoint catalog.
Usage
/digest <url>
Examples
# Evaluate a library
/digest https://github.com/owner/cool-library
# Summarize an article
/digest https://blog.example.com/microservices-patterns
# Overview documentation
/digest https://docs.example.com
Content Type Detection
| Type | Signals | Output Style | |------|---------|-------------| | Library/Tool | GitHub repo, npm page, PyPI | Feature matrix, ecosystem health, recommendation | | Blog/Article | Single long-form content | Key takeaways, relevance assessment | | Documentation | Multi-page, navigation structure | Structure map, coverage assessment, quality | | API Reference | Endpoints, methods, params | Endpoint catalog, auth info, SDK availability | | Comparison | Tables, vs, alternatives | Feature matrix, winner per category | | Tutorial | Step-by-step, code blocks | Prerequisites, steps summary, outcome |
Output Templates
Library Evaluation
# Library: [name]
> Source: [URL] | Stars: [X] | Last commit: [date]
## What It Does
[1-2 sentence description]
## Key Features
- Feature 1
- Feature 2
## Ecosystem Health
| Metric | Value |
|--------|-------|
| GitHub Stars | X |
| Weekly Downloads | X |
| Last Release | date |
| Open Issues | X |
| Contributors | X |
## API Surface
[Key classes/functions/exports]
## Verdict
[Use when... Don't use when... Alternatives: ...]
Article Summary
# Summary: [title]
> Source: [URL] | Author: [name] | Date: [date]
## Key Takeaways
1. [Point 1]
2. [Point 2]
3. [Point 3]
## Relevance
[How this applies to current project/context]
## Action Items
- [What to do based on this]
Rules
- Auto-detect, don't ask user for content type
- Keep summaries under 500 words
- Always include source URL and date
- For libraries: check last commit date, flag if > 6 months
- For articles: check publication date, flag if > 1 year
- Confidence rating on every assessment
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