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Get Started Free →Use when Codex is working on a repo or task that is scoped to an OrgX initiative, workstream, milestone, task, blocker, or decision and needs to use OrgX MCP as the source of truth.
.claude/skills/hashgraph-online-orgx-initiative-ops/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 264% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 295% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 163% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 8% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 100% | 0% |
Use this skill when the task is tied to OrgX execution state rather than just local code.
get_operator_chronicle firstwhen available; it is the canonical decision, artifact, PR, goal, gap, and priority readout.
get_operator_chronicle but theactive AI client session has a stale callable tool list, immediately use orgx_recommend or _orgx_recommend with mode: "morning_brief" and report the returned reportingNarrative.briefMarkdown. Do not wait for the client to reconnect before answering the operator.
source_client=codex whenever the tool supports client attribution.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-23 | pass→pass | 13,560 | 6,818 | -50% | 1 | 1 | 0% | 1,740 | 1,562 | -10% | 0 | 0 | — |
case-01 | fail→fail | 24,919 | 11,247 | -55% | 1 | 1 | 0% | 1,876 | 796 | -58% | 0 | 0 | — |
case-02 | fail→pass | 6,897 | 26,922 | +290% | 1 | 1 | 0% | 987 | 3,594 | +264% | 0 | 0 | — |
case-03 | fail→fail | 11,288 | 19,446 | +72% | 1 | 1 | 0% | 2,078 | 871 | -58% | 0 | 0 | — |
case-04 | fail→fail | 10,853 | 21,440 | +98% | 1 | 1 | 0% | 840 | 843 | +0% | 0 | 0 | — |
case-05 | fail→fail | 11,431 | 19,581 | +71% | 1 | 1 | 0% | 2,133 | 1,203 | -44% | 0 | 0 | — |
case-06 | fail→pass | 6,246 | 23,300 | +273% | 1 | 1 | 0% | 506 | 1,997 | +295% | 0 | 0 | — |
case-07 | fail→fail | 3,891 | 19,854 | +410% | 1 | 1 | 0% | 604 | 818 | +35% | 0 | 0 | — |
case-08 | fail→pass | 15,592 | 10,918 | -30% | 1 | 1 | 0% | 925 | 2,433 | +163% | 0 | 0 | — |
case-09 | fail→fail | 3,878 | 33,612 | +767% | 1 | 1 | 0% | 605 | 4,735 | +683% | 0 | 0 | — |
case-10 | fail→fail | 6,330 | 18,556 | +193% | 1 | 1 | 0% | 948 | 794 | -16% | 0 | 0 | — |
case-11 | fail→pass | 19,990 | 13,123 | -34% | 1 | 1 | 0% | 2,301 | 2,475 | +8% | 0 | 0 | — |
case-17 | fail→fail | 24,870 | 23,991 | -4% | 1 | 1 | 0% | 3,223 | 1,803 | -44% | 0 | 0 | — |
case-12 | fail→fail | 7,900 | 14,527 | +84% | 1 | 1 | 0% | 388 | 1,147 | +196% | 0 | 0 | — |
case-13 | fail→pass | 8,183 | 5,615 | -31% | 1 | 1 | 0% | 640 | 1,279 | +100% | 0 | 0 | — |
case-14 | fail→fail | 15,866 | 2,874 | -82% | 1 | 1 | 0% | 1,678 | 925 | -45% | 0 | 0 | — |
case-15 | fail→fail | 5,988 | 13,160 | +120% | 1 | 1 | 0% | 448 | 1,177 | +163% | 0 | 0 | — |
case-16 | pass→pass | 24,555 | 15,146 | -38% | 1 | 1 | 0% | 2,333 | 2,701 | +16% | 0 | 0 | — |
case-18 | fail→fail | 14,498 | 36,029 | +149% | 1 | 1 | 0% | 1,755 | 3,216 | +83% | 0 | 0 | — |
case-19 | pass→pass | 14,774 | 4,801 | -68% | 1 | 1 | 0% | 1,438 | 864 | -40% | 0 | 0 | — |
case-20 | pass→fail | 8,828 | 15,996 | +81% | 1 | 1 | 0% | 1,743 | 1,140 | -35% | 0 | 0 | — |
case-21 | pass→pass | 7,736 | 7,869 | +2% | 1 | 1 | 0% | 1,415 | 1,734 | +23% | 0 | 0 | — |
case-22 | pass→pass | 16,048 | 25,822 | +61% | 1 | 1 | 0% | 3,245 | 3,356 | +3% | 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, and 14 counted toward the lift figure. The other 9 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 +17 percentage points is the difference between those two pass rates over the 14 comparable cases. 2 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.