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Get Started Free →Scans HN, Lobsters, Reddit, and tech blogs for community experience reports. Use when gathering practitioner opinions on a technology or approach.
.claude/skills/athola-discourse/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | -48% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -40% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -59% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -22% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -70% | 0% |
/tome:papers)/tome:code-search)Scan community channels for discussions on a topic.
tome.channels.discourse.* functions
tech blogs) queried per invocation
hn.algolia.com(WebFetch); WebSearch used as fallback if the API is unreachable
source field identifyingwhich channel (HN, Lobsters, Reddit, or blog) it came from
the failure is reported explicitly rather than returning fabricated or empty findings
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-16 | fail→fail | 19,683 | 11,736 | -40% | 1 | 1 | 0% | 2,909 | 1,019 | -65% | 0 | 0 | — |
case-01 | fail→fail | 16,449 | 9,797 | -40% | 1 | 1 | 0% | 2,506 | 908 | -64% | 0 | 0 | — |
case-02 | fail→fail | 16,097 | 9,645 | -40% | 1 | 1 | 0% | 2,387 | 712 | -70% | 0 | 0 | — |
case-03 | fail→fail | 17,824 | 7,929 | -56% | 1 | 1 | 0% | 2,539 | 881 | -65% | 0 | 0 | — |
case-04 | fail→pass | 21,655 | 8,294 | -62% | 1 | 1 | 0% | 3,074 | 1,605 | -48% | 0 | 0 | — |
case-05 | fail→fail | 14,302 | 13,576 | -5% | 1 | 1 | 0% | 2,747 | 2,955 | +8% | 0 | 0 | — |
case-06 | fail→fail | 19,747 | 42,468 | +115% | 1 | 1 | 0% | 3,061 | 3,482 | +14% | 0 | 0 | — |
case-07 | pass→pass | 4,887 | 3,334 | -32% | 1 | 1 | 0% | 796 | 760 | -5% | 0 | 0 | — |
case-08 | pass→pass | 14,033 | 10,158 | -28% | 1 | 1 | 0% | 2,541 | 2,038 | -20% | 0 | 0 | — |
case-09 | fail→pass | 19,349 | 5,811 | -70% | 1 | 1 | 0% | 2,196 | 1,326 | -40% | 0 | 0 | — |
case-10 | fail→pass | 11,158 | 2,561 | -77% | 1 | 1 | 0% | 1,816 | 741 | -59% | 0 | 0 | — |
case-11 | fail→fail | 8,887 | 1,357 | -85% | 1 | 1 | 0% | 1,284 | 508 | -60% | 0 | 0 | — |
case-12 | fail→fail | 7,568 | 1,840 | -76% | 1 | 1 | 0% | 1,025 | 611 | -40% | 0 | 0 | — |
case-13 | pass→pass | 8,415 | 3,094 | -63% | 1 | 1 | 0% | 1,187 | 757 | -36% | 0 | 0 | — |
case-14 | fail→pass | 17,927 | 10,713 | -40% | 1 | 1 | 0% | 2,570 | 1,994 | -22% | 0 | 0 | — |
case-15 | fail→pass | 12,124 | 1,664 | -86% | 1 | 1 | 0% | 1,687 | 498 | -70% | 0 | 0 | — |
case-17 | fail→fail | 15,612 | 8,105 | -48% | 1 | 1 | 0% | 2,293 | 692 | -70% | 0 | 0 | — |
case-18 | fail→fail | 34,086 | 8,472 | -75% | 1 | 1 | 0% | 2,573 | 654 | -75% | 0 | 0 | — |
case-19 | fail→fail | 18,916 | 10,659 | -44% | 1 | 1 | 0% | 2,763 | 969 | -65% | 0 | 0 | — |
case-20 | fail→fail | 17,753 | 10,335 | -42% | 1 | 1 | 0% | 2,960 | 968 | -67% | 0 | 0 | — |
case-21 | fail→fail | 14,427 | 9,849 | -32% | 1 | 1 | 0% | 2,001 | 818 | -59% | 0 | 0 | — |
case-22 | fail→fail | 18,517 | 8,836 | -52% | 1 | 1 | 0% | 2,647 | 650 | -75% | 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. 22 cases were attempted, and 12 counted toward the lift figure. The other 10 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +23 percentage points is the difference between those two pass rates over the 12 comparable cases. 3 cases got worse with the skill loaded, and they are 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.
Other measured skills in the registry, with their headline benchmark lift.