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Get Started Free →Canonical PR/Issue triage pack combining repo review queues with work tracker context and approval-gated write-backs.
.claude/skills/mkurman-pr-issue-triage/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -36% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -21% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -35% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -13% | 0% |
I want one triage view across repo review items and issue tracker work, so I can see stale, blocked, and actionable items without manually stitching together GitHub/GitLab and Linear/Jira.
github or gitlablinear or jirarepo_connector: github or gitlabtracker_connector: linear, jira, or noneowner / repo or equivalent project coordinatesinclude_writeback_suggestions: booleanstale_days: integer thresholdapproval-requiredSchedule as a weekday triage routine or on-demand review block. Example payload description:
Run the canonical PR/Issue Triage pack for the main repo, merge repo/tracker context, and surface approval-gated write-back suggestions.
Run PR/Issue Triage for owner/repo using GitHub plus Linear. Show stale PRs, blocked issues, and suggested labels/comments, but do not perform write-backs without approval.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | pass→pass | 10,255 | 11,703 | +14% | 1 | 1 | 0% | 1,584 | 2,607 | +65% | 0 | 0 | — |
case-04 | fail→pass | 18,886 | 11,595 | -39% | 1 | 1 | 0% | 2,456 | 2,536 | +3% | 0 | 0 | — |
case-14 | pass→pass | 12,563 | 7,134 | -43% | 1 | 1 | 0% | 1,945 | 1,651 | -15% | 0 | 0 | — |
case-01 | pass→pass | 12,836 | 63,712 | +396% | 1 | 1 | 0% | 1,473 | 1,242 | -16% | 0 | 0 | — |
case-02 | pass→pass | 11,280 | 10,904 | -3% | 1 | 1 | 0% | 1,178 | 2,573 | +118% | 0 | 0 | — |
case-05 | pass→pass | 19,095 | 15,793 | -17% | 1 | 1 | 0% | 2,887 | 3,304 | +14% | 0 | 0 | — |
case-06 | fail→pass | 13,598 | 6,234 | -54% | 1 | 1 | 0% | 2,219 | 1,426 | -36% | 0 | 0 | — |
case-07 | fail→pass | 19,060 | 10,203 | -46% | 1 | 1 | 0% | 2,950 | 2,316 | -21% | 0 | 0 | — |
case-08 | pass→pass | 18,694 | 16,671 | -11% | 1 | 1 | 0% | 2,884 | 3,362 | +17% | 0 | 0 | — |
case-09 | pass→pass | 14,050 | 9,478 | -33% | 1 | 1 | 0% | 2,257 | 2,063 | -9% | 0 | 0 | — |
case-10 | pass→pass | 17,076 | 14,205 | -17% | 1 | 1 | 0% | 2,821 | 2,898 | +3% | 0 | 0 | — |
case-11 | pass→pass | 17,156 | 10,866 | -37% | 1 | 1 | 0% | 2,827 | 2,342 | -17% | 0 | 0 | — |
case-12 | fail→pass | 8,240 | 1,817 | -78% | 1 | 1 | 0% | 1,256 | 821 | -35% | 0 | 0 | — |
case-13 | fail→pass | 9,081 | 4,114 | -55% | 1 | 1 | 0% | 1,361 | 1,182 | -13% | 0 | 0 | — |
case-15 | pass→pass | 17,407 | 8,914 | -49% | 1 | 1 | 0% | 2,510 | 2,044 | -19% | 0 | 0 | — |
case-16 | pass→pass | 12,928 | 6,521 | -50% | 1 | 1 | 0% | 1,985 | 1,517 | -24% | 0 | 0 | — |
case-17 | fail→pass | 2,353 | 1,721 | -27% | 1 | 1 | 0% | 281 | 740 | +163% | 0 | 0 | — |
case-18 | fail→pass | 2,353 | 2,192 | -7% | 1 | 1 | 0% | 310 | 798 | +157% | 0 | 0 | — |
case-19 | pass→pass | 12,031 | 2,313 | -81% | 1 | 1 | 0% | 2,064 | 926 | -55% | 0 | 0 | — |
case-20 | pass→pass | 11,087 | 9,871 | -11% | 1 | 1 | 0% | 2,083 | 2,355 | +13% | 0 | 0 | — |
case-21 | pass→pass | 3,654 | 3,483 | -5% | 1 | 1 | 0% | 639 | 1,146 | +79% | 0 | 0 | — |
case-22 | pass→pass | 4,793 | 4,490 | -6% | 1 | 1 | 0% | 772 | 1,379 | +79% | 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. The headline lift of +32 percentage points is the difference between those two pass rates over the 22 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.