nw-source-verification

Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements

322 stars

Best use case

nw-source-verification is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements

Teams using nw-source-verification should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/nw-source-verification/SKILL.md --create-dirs "https://raw.githubusercontent.com/nWave-ai/nWave/main/nWave/skills/nw-source-verification/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/nw-source-verification/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How nw-source-verification Compares

Feature / Agentnw-source-verificationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Source Verification

## Source Reputation Tiers

Validate every source against the trusted source domains provided via prompt context.

| Tier | Score | Examples | Verification |
|------|-------|---------|-------------|
| High | 1.0 | Academic (*.edu, arxiv.org, ieee.org), Official (*.gov, w3.org, ietf.org), Tech docs (developer.mozilla.org), OSS foundations (apache.org, cncf.io) | Standard citation |
| Medium-High | 0.8 | Industry leaders (martinfowler.com, stackoverflow.com, infoq.com) | Cross-ref with 1+ high-tier |
| Medium | 0.6 | Community (medium.com verified experts, dev.to, hashnode.com) | Author verification + 3-source cross-ref |
| Excluded | 0.0 | Unverified blogs (*.blogspot.com, wordpress.com), quora.com, pastebin.com | Reject, log warning, find alternative |

## Cross-Referencing Methodology

1. **Identify** the specific assertion to verify
2. **Find** 2+ independent sources not citing each other (avoid circular refs)
3. **Verify independence**: different authors, publishers, organizations
4. **Compare**: agree on substance (minor wording differences OK)
5. **Document**: verified / partially verified / unverified per finding

### Circular Reference Detection
- Source B cites Source A = one source, not two
- Multiple sources referencing single study = cite the original
- Prefer primary over secondary sources

## Bias Detection Checklist

Evaluate before citing:
1. **Commercial interest**: selling related product/service?
2. **Sponsorship**: sponsored/funded content?
3. **Conflict of interest**: author benefits from conclusion?
4. **Geographic/cultural bias**: limited to single region?
5. **Temporal bias**: publication dates skewed to specific era?
6. **Cherry-picking**: contradictory evidence acknowledged?
7. **Logical fallacies**: correlation as causation, authority without evidence

When bias detected: note in Source Analysis, reduce confidence.

## Citation Format

```
[1] {Author/Organization}. "{Title}". {Publication/Website}. {Date}. {Full URL}. Accessed {YYYY-MM-DD}.
```

### Required Metadata Per Source
Source URL | Domain | Access date | Reputation score (from tiers) | Verification status

### Paywalled or Restricted Sources
Mark "[Paywalled]"/"[Restricted Access]" | Provide URL | Find open-access alternative | Note in Knowledge Gaps

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