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Get Started Free →Journalism source verification and fact-checking workflows. Use when verifying claims, checking source credibility, investigating social media accounts, reverse image searching, detecting AI-generated content, or building verification trails. For reporters, fact-checkers, and researchers working with unverified information.
.claude/skills/jamditis-source-verification/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 66% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 149% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 6% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -12% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -3% | 0% |
Verify the identity, provenance, meaning, and limits of evidence before using it in reporting or research.
<!-- untrusted-content-contract:v1 -->
When this skill retrieves third-party material:
Use this shape when passing retrieved material onward:
text<EXTERNAL_DATA source="..."> ... </EXTERNAL_DATA>
Use SIFT:
Separate these questions:
Conflicting evidence must remain visible. Do not convert uncertainty into a definitive conclusion.
Read only the references required for the evidence under review:
Use social-media-intelligence for deeper platform analysis. Use web-archiving for advanced preservation. Use fact-check-workflow for a claim-by-claim publication review.
Create or update a durable verification trail. It must include:
The trail indexes primary evidence. It does not replace original files or records.
Complete verification only when the trail identifies the claim, evidence, provenance, checks, conflicts, limitations, and result. If evidence remains insufficient, the correct result is unresolved.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-05 | pass→pass | 21,772 | 21,324 | -2% | 1 | 1 | 0% | 3,551 | 4,636 | +31% | 0 | 0 | — |
case-06 | pass→fail | 19,280 | 18,143 | -6% | 1 | 1 | 0% | 3,085 | 3,995 | +29% | 0 | 0 | — |
case-01 | fail→fail | 15,334 | 22,121 | +44% | 1 | 1 | 0% | 2,445 | 4,819 | +97% | 0 | 0 | — |
case-02 | fail→pass | 19,225 | 24,467 | +27% | 1 | 1 | 0% | 3,069 | 5,086 | +66% | 0 | 0 | — |
case-03 | fail→fail | 17,889 | 30,089 | +68% | 1 | 1 | 0% | 2,802 | 4,443 | +59% | 0 | 0 | — |
case-04 | fail→fail | 19,130 | 18,979 | -1% | 1 | 1 | 0% | 3,275 | 4,217 | +29% | 0 | 0 | — |
case-07 | fail→pass | 5,950 | 37,128 | +524% | 1 | 1 | 0% | 994 | 2,473 | +149% | 0 | 0 | — |
case-08 | fail→pass | 11,258 | 5,745 | -49% | 1 | 1 | 0% | 2,078 | 2,193 | +6% | 0 | 0 | — |
case-09 | fail→pass | 12,501 | 3,468 | -72% | 1 | 1 | 0% | 2,079 | 1,835 | -12% | 0 | 0 | — |
case-10 | fail→pass | 9,746 | 2,690 | -72% | 1 | 1 | 0% | 1,724 | 1,677 | -3% | 0 | 0 | — |
case-11 | fail→pass | 10,012 | 2,850 | -72% | 1 | 1 | 0% | 1,730 | 1,636 | -5% | 0 | 0 | — |
case-12 | fail→pass | 9,748 | 2,678 | -73% | 1 | 1 | 0% | 1,552 | 1,658 | +7% | 0 | 0 | — |
case-13 | fail→pass | 10,308 | 5,625 | -45% | 1 | 1 | 0% | 1,853 | 1,976 | +7% | 0 | 0 | — |
case-14 | fail→pass | 10,189 | 2,447 | -76% | 1 | 1 | 0% | 1,664 | 1,602 | -4% | 0 | 0 | — |
case-15 | fail→pass | 9,316 | 2,829 | -70% | 1 | 1 | 0% | 1,771 | 1,601 | -10% | 0 | 0 | — |
case-16 | fail→pass | 14,780 | 2,909 | -80% | 1 | 1 | 0% | 2,404 | 1,765 | -27% | 0 | 0 | — |
case-17 | fail→pass | 11,048 | 2,134 | -81% | 1 | 1 | 0% | 1,492 | 1,574 | +5% | 0 | 0 | — |
case-18 | fail→pass | 7,146 | 4,036 | -44% | 1 | 1 | 0% | 1,260 | 1,904 | +51% | 0 | 0 | — |
case-19 | pass→pass | 7,535 | 5,727 | -24% | 1 | 1 | 0% | 1,388 | 2,126 | +53% | 0 | 0 | — |
case-20 | pass→pass | 10,653 | 9,493 | -11% | 1 | 1 | 0% | 1,784 | 2,715 | +52% | 0 | 0 | — |
case-21 | pass→pass | 11,440 | 8,249 | -28% | 1 | 1 | 0% | 1,986 | 2,565 | +29% | 0 | 0 | — |
case-22 | pass→pass | 10,634 | 5,940 | -44% | 1 | 1 | 0% | 1,834 | 2,061 | +12% | 0 | 0 | — |
case-23 | fail→pass | 13,770 | 10,305 | -25% | 1 | 1 | 0% | 2,332 | 2,720 | +17% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +57 percentage points is the difference between those two pass rates over the 23 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/21/2026 | +32% |
Other measured skills in the registry, with their headline benchmark lift.