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Get Started Free →Execute Flexport incident response for API outages, webhook failures, and supply chain data sync issues with triage and mitigation steps. Trigger: "flexport incident", "flexport outage", "flexport down", "flexport emergency".
.claude/skills/jeremylongshore-flexport-incident-runbook/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 25% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -2% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 8% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 4% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 30% | 0% |
Preserve freight correctness first. Freeze uncertain mutations, separate provider delivery from local processing, and reconstruct affected state with documented resource/event reads.
Disable automatic bookings and affected writes. Keep authenticated webhook acceptance only if durable enqueue and deduplication remain correct.
Identify first/last bad receipt by surface, operation, release, credential alias, and version without examining broad sensitive payloads.
Test OAuth, REST read, MCP connection, webhook ingress, queue processing, and downstream state independently.
Use /events or affected resource reads to compare provider state with durable local operation keys. Do not assume Flexport exposes a webhook replay endpoint.
Reprocess authenticated durable events or apply approved state corrections exactly once; reconcile uncertain creates/bookings before retry.
Restore traffic by cohort, verify the full incident window, rotate exposed credentials if needed, and add a sanitized regression fixture.
REST calls authenticate with a cached OAuth 2.0 client-credentials Bearer token using audience https://api.flexport.com, or an explicitly accepted broad API key. Use distinct credentials per workload and never log credentials or tokens. MCP calls use the authenticated connection to https://mcp.flexport.com/mcp and remain subject to each tool's documented account permissions.
Use Read and Grep for discovery and evidence. Use Write or Edit only for the approved artifact, code, configuration, test, or receipt described by this workflow; do not make an unapproved Flexport-side change.
Return a machine-reviewable receipt in this shape; adapt the operation values, but never place credentials or provider payloads in it:
yamlsurface: rest-v3 operation: shipment-read decision: approved outcome: verified evidence: release_sha: recorded-out-of-band provider_reference: redacted rollback_owner: logistics-platform
A receiver deployment parsed bodies before signature validation and dropped events. The team restores the prior release, queries the bounded event/resource window, deduplicates by durable operation identity, and backfills only missing local transitions.
| Failure | Response | | --- | --- | | Provider reads unavailable | Maintain the mutation freeze and preserve the reconciliation window. | | Duplicate business action found | Stop workers and choose one authoritative provider resource. | | Event type newly additive | Update tolerant routing and replay only authenticated durable items. | | Incident needs sensitive payload | Escalate access and minimize fields rather than copying broad logs. |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 10,196 | 10,366 | +2% | 1 | 1 | 0% | 1,659 | 2,075 | +25% | 0 | 0 | — |
case-02 | fail→pass | 19,886 | 7,600 | -62% | 1 | 1 | 0% | 2,617 | 2,572 | -2% | 0 | 0 | — |
case-03 | fail→fail | 18,656 | 13,093 | -30% | 1 | 1 | 0% | 2,977 | 3,226 | +8% | 0 | 0 | — |
case-04 | pass→pass | 22,299 | 21,221 | -5% | 1 | 1 | 0% | 3,399 | 4,549 | +34% | 0 | 0 | — |
case-05 | pass→pass | 20,078 | 19,559 | -3% | 1 | 1 | 0% | 3,143 | 3,302 | +5% | 0 | 0 | — |
case-06 | pass→pass | 19,054 | 16,288 | -15% | 1 | 1 | 0% | 2,789 | 3,322 | +19% | 0 | 0 | — |
case-07 | fail→pass | 15,358 | 8,730 | -43% | 1 | 1 | 0% | 1,675 | 1,802 | +8% | 0 | 0 | — |
case-08 | fail→pass | 18,343 | 12,534 | -32% | 1 | 1 | 0% | 2,282 | 2,368 | +4% | 0 | 0 | — |
case-09 | fail→pass | 13,176 | 8,622 | -35% | 1 | 1 | 0% | 1,270 | 1,656 | +30% | 0 | 0 | — |
case-10 | pass→pass | 11,395 | 1,736 | -85% | 1 | 1 | 0% | 916 | 1,337 | +46% | 0 | 0 | — |
case-11 | pass→pass | 13,410 | 8,862 | -34% | 1 | 1 | 0% | 1,535 | 1,812 | +18% | 0 | 0 | — |
case-12 | fail→pass | 21,142 | 11,665 | -45% | 1 | 1 | 0% | 3,403 | 3,132 | -8% | 0 | 0 | — |
case-13 | pass→pass | 12,871 | 8,844 | -31% | 1 | 1 | 0% | 1,114 | 1,509 | +35% | 0 | 0 | — |
case-14 | fail→pass | 9,756 | 7,413 | -24% | 1 | 1 | 0% | 1,514 | 2,183 | +44% | 0 | 0 | — |
case-15 | fail→pass | 12,048 | 2,318 | -81% | 1 | 1 | 0% | 1,096 | 1,484 | +35% | 0 | 0 | — |
case-16 | fail→pass | 10,880 | 3,274 | -70% | 1 | 1 | 0% | 862 | 1,462 | +70% | 0 | 0 | — |
case-17 | fail→pass | 16,800 | 7,471 | -56% | 1 | 1 | 0% | 2,643 | 2,494 | -6% | 0 | 0 | — |
case-18 | fail→pass | 19,958 | 2,857 | -86% | 1 | 1 | 0% | 2,446 | 1,549 | -37% | 0 | 0 | — |
case-19 | fail→pass | 5,854 | 2,780 | -53% | 1 | 1 | 0% | 1,167 | 1,516 | +30% | 0 | 0 | — |
case-20 | fail→pass | 12,548 | 17,923 | +43% | 1 | 1 | 0% | 2,139 | 3,206 | +50% | 0 | 0 | — |
case-21 | fail→pass | 20,444 | 6,800 | -67% | 1 | 1 | 0% | 850 | 1,398 | +64% | 0 | 0 | — |
case-22 | pass→pass | 13,243 | 6,748 | -49% | 1 | 1 | 0% | 1,709 | 1,413 | -17% | 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 21 counted toward the lift figure. The other 1 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 +64 percentage points is the difference between those two pass rates over the 21 comparable cases.
The publisher has shipped newer versions since this run, so these numbers describe v1, not the version currently listed.
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.