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Get Started Free →AI news tracking skill that monitors 80+ entities across 6 free sources (Reddit, HN, GitHub, HuggingFace, arXiv, X/Twitter). Generates scored daily reports with infographics and message digests. Invoke via /morning-ai.
.claude/skills/davepoon-morning-ai/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | -47% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -56% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -65% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -47% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -55% | 0% |
Daily AI news tracker that collects updates from 80+ entities across 6 sources, scores and deduplicates them, and generates a structured Markdown report.
MorningAI requires its full repository for data collection scripts:
bash# Install as a Claude Code plugin git clone https://github.com/octo-patch/MorningAI.git ~/.claude/plugins/MorningAI # Or install as a skill git clone https://github.com/octo-patch/MorningAI.git cd MorningAI
/morning-ai/morning-ai --lang zh
/morning-ai --depth deep
/morning-ai --exclude Funding| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-17 | pass→pass | 6,184 | 1,325 | -79% | 1 | 1 | 0% | 1,069 | 488 | -54% | 0 | 0 | — |
case-01 | fail→fail | 14,193 | 19,415 | +37% | 1 | 1 | 0% | 2,287 | 3,472 | +52% | 0 | 0 | — |
case-02 | fail→fail | 17,121 | 11,930 | -30% | 1 | 1 | 0% | 3,055 | 2,416 | -21% | 0 | 0 | — |
case-03 | fail→pass | 7,464 | 1,827 | -76% | 1 | 1 | 0% | 1,223 | 654 | -47% | 0 | 0 | — |
case-04 | fail→pass | 7,972 | 2,409 | -70% | 1 | 1 | 0% | 1,333 | 592 | -56% | 0 | 0 | — |
case-05 | pass→pass | 7,379 | 1,488 | -80% | 1 | 1 | 0% | 1,133 | 564 | -50% | 0 | 0 | — |
case-06 | pass→pass | 9,182 | 2,669 | -71% | 1 | 1 | 0% | 1,658 | 774 | -53% | 0 | 0 | — |
case-07 | fail→pass | 7,577 | 1,063 | -86% | 1 | 1 | 0% | 1,266 | 447 | -65% | 0 | 0 | — |
case-08 | pass→pass | 9,856 | 3,384 | -66% | 1 | 1 | 0% | 1,925 | 740 | -62% | 0 | 0 | — |
case-09 | fail→pass | 8,362 | 1,843 | -78% | 1 | 1 | 0% | 1,261 | 664 | -47% | 0 | 0 | — |
case-10 | pass→pass | 5,877 | 1,492 | -75% | 1 | 1 | 0% | 1,005 | 562 | -44% | 0 | 0 | — |
case-11 | pass→pass | 14,018 | 7,090 | -49% | 1 | 1 | 0% | 2,505 | 1,470 | -41% | 0 | 0 | — |
case-12 | fail→pass | 7,034 | 1,322 | -81% | 1 | 1 | 0% | 1,161 | 528 | -55% | 0 | 0 | — |
case-13 | pass→pass | 8,525 | 1,867 | -78% | 1 | 1 | 0% | 1,481 | 624 | -58% | 0 | 0 | — |
case-14 | fail→pass | 6,098 | 1,192 | -80% | 1 | 1 | 0% | 969 | 503 | -48% | 0 | 0 | — |
case-15 | pass→pass | 5,454 | 1,434 | -74% | 1 | 1 | 0% | 804 | 545 | -32% | 0 | 0 | — |
case-16 | fail→pass | 5,169 | 1,289 | -75% | 1 | 1 | 0% | 926 | 587 | -37% | 0 | 0 | — |
case-18 | fail→pass | 8,562 | 2,378 | -72% | 1 | 1 | 0% | 1,447 | 607 | -58% | 0 | 0 | — |
case-19 | fail→pass | 6,080 | 1,726 | -72% | 1 | 1 | 0% | 1,062 | 575 | -46% | 0 | 0 | — |
case-20 | fail→pass | 10,141 | 3,448 | -66% | 1 | 1 | 0% | 1,684 | 1,024 | -39% | 0 | 0 | — |
case-21 | fail→pass | 11,113 | 8,461 | -24% | 1 | 1 | 0% | 2,050 | 2,008 | -2% | 0 | 0 | — |
case-22 | fail→pass | 14,887 | 12,399 | -17% | 1 | 1 | 0% | 2,971 | 2,848 | -4% | 0 | 0 | — |
case-23 | fail→pass | 10,943 | 7,519 | -31% | 1 | 1 | 0% | 1,686 | 1,556 | -8% | 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.
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.
Other measured skills in the registry, with their headline benchmark lift.