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Get Started Free →Use when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop.
.claude/skills/hashgraph-online-runtime-evidence-and-tracing/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -49% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -53% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 40% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 24% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 4% | 0% |
Make runtime validation auditable by tying observed behavior to runtime evidence through stable IDs and artifacts.
Agents should not only say they tested something; they should leave run IDs, request IDs, logs, screenshots, interaction records, or traces. For shared harness terms, see ../../references/harness-patterns.md; when evidence surfaces are absent, use references/build-when-missing.md. For neutral runtime profiles and redaction policy, see references/runtime-profile-policy.md.
X-Request-ID and X-Harness-Run-ID.references/build-when-missing.md.artifacts/runs/<run_id>/ with manifest, summary, logs, network, screenshots, and trace files.markdown# Runtime Evidence And Tracing ## Detected Mapping - runtime-evidence: - validation: - ledger: ## ID Contract - Run ID: - Request ID: - Header propagation: ## Artifact Bundle - ## Collection Flow 1. 2. 3. ## Failure Classification - ## PR / Ledger Reference -
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 47,522 | 25,655 | -46% | 1 | 1 | 0% | 8,292 | 4,259 | -49% | 0 | 0 | — |
case-02 | fail→pass | 71,692 | 22,336 | -69% | 1 | 1 | 0% | 8,282 | 3,904 | -53% | 0 | 0 | — |
case-03 | pass→pass | 60,210 | 27,558 | -54% | 1 | 1 | 0% | 8,275 | 3,780 | -54% | 0 | 0 | — |
case-04 | fail→pass | 18,372 | 18,760 | +2% | 1 | 1 | 0% | 2,967 | 4,152 | +40% | 0 | 0 | — |
case-05 | fail→pass | 21,076 | 14,907 | -29% | 1 | 1 | 0% | 2,722 | 3,369 | +24% | 0 | 0 | — |
case-06 | pass→pass | 14,577 | 16,185 | +11% | 1 | 1 | 0% | 1,547 | 2,835 | +83% | 0 | 0 | — |
case-07 | pass→pass | 10,044 | 21,926 | +118% | 1 | 1 | 0% | 1,291 | 2,569 | +99% | 0 | 0 | — |
case-08 | pass→pass | 11,889 | 7,657 | -36% | 1 | 1 | 0% | 1,792 | 1,956 | +9% | 0 | 0 | — |
case-09 | pass→pass | 16,675 | 16,110 | -3% | 1 | 1 | 0% | 1,840 | 2,628 | +43% | 0 | 0 | — |
case-10 | pass→pass | 51,475 | 24,190 | -53% | 1 | 1 | 0% | 2,872 | 3,672 | +28% | 0 | 0 | — |
case-11 | fail→pass | 22,999 | 11,779 | -49% | 1 | 1 | 0% | 2,553 | 2,659 | +4% | 0 | 0 | — |
case-12 | pass→pass | 13,836 | 30,280 | +119% | 1 | 1 | 0% | 2,132 | 3,084 | +45% | 0 | 0 | — |
case-13 | fail→pass | 14,213 | 14,016 | -1% | 1 | 1 | 0% | 1,496 | 2,298 | +54% | 0 | 0 | — |
case-14 | fail→pass | 18,287 | 19,792 | +8% | 1 | 1 | 0% | 2,496 | 2,971 | +19% | 0 | 0 | — |
case-15 | fail→pass | 20,745 | 20,230 | -2% | 1 | 1 | 0% | 2,891 | 3,364 | +16% | 0 | 0 | — |
case-16 | pass→pass | 13,256 | 9,416 | -29% | 1 | 1 | 0% | 1,259 | 2,157 | +71% | 0 | 0 | — |
case-17 | pass→pass | 21,126 | 13,408 | -37% | 1 | 1 | 0% | 2,365 | 2,020 | -15% | 0 | 0 | — |
case-18 | pass→pass | 20,786 | 26,686 | +28% | 1 | 1 | 0% | 3,420 | 4,766 | +39% | 0 | 0 | — |
case-19 | pass→pass | 14,907 | 7,339 | -51% | 1 | 1 | 0% | 2,014 | 1,997 | -1% | 0 | 0 | — |
case-20 | pass→pass | 15,909 | 18,321 | +15% | 1 | 1 | 0% | 3,027 | 4,336 | +43% | 0 | 0 | — |
case-21 | pass→pass | 19,376 | 16,666 | -14% | 1 | 1 | 0% | 2,717 | 2,773 | +2% | 0 | 0 | — |
case-22 | pass→pass | 19,357 | 20,961 | +8% | 1 | 1 | 0% | 2,211 | 3,629 | +64% | 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 +36 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.