codex smoke: refreshed api secrets

[Pigbibi]

Temporary smoke test after refreshing OpenAI/Anthropic API fallback secrets.

Expected mode: review_only; no source repository changes requested.

[quantcrossrepoautomation]

API Monthly Review

Codex service failed with exit code 1: Codex audit service job failed [unknown_failure]: codex exec failed: dates = [pd.Timestamp("2024-01-31"), pd.Timestamp("2024-02-29")] symbols = ["AAA", "BBB", "CCC"] index = pd.MultiIndex.from_product([dates, symbols], names=["date", "symbol"]) panel = pd.DataFrame(index=index) panel["in_universe"] = True panel["final_score"] = [ 0.9, 0.8, 0.1, 0.2, 0.95, 0.85, ] panel["future_return_30"] = [ 0.4, 0.2, 0.1, 0.0, 0.1, 0.5, ] config = { "export": {"live_pool_siz.... Using the configured API fallback reviewers.

OpenAI Review

API Monthly Review

English

Release Consistency

• This is a smoke-test issue after refreshing OpenAI/Anthropic fallback secrets, not a strategy or model release.
• The report is consistent with a review-only monthly snapshot workflow and does not imply changes to production logic.
• No HK snapshot promotion gate checks are required for this repository, since the target repo is CryptoLivePoolPipelines, not HkEquitySnapshotPipelines.

Evidence Gaps

• The issue body does not include execution evidence beyond the stated secret refresh and smoke-test intent.
• Missing details: which API paths were exercised, whether fallback behavior was actually verified, timestamps, logs, or any success/failure artifacts.
• No provenance material is attached for the refreshed secrets, so it is unclear whether the test covered all relevant runtime environments.

Downstream Impact

• If fallback secrets were refreshed correctly, the main downstream benefit is reduced risk of API-auth failures in smoke or live-adjacent checks.
• Without explicit run logs, it is not possible to confirm whether any dependent automation, alerting, or notification paths were validated.
• Low impact on strategy content; higher relevance to operational reliability and secret rotation continuity.

Operator Action Items

• Confirm the smoke test produced verifiable logs or job output showing successful use of the refreshed fallback credentials.
• Attach a short evidence bundle: execution timestamp, environment, API endpoint exercised, and pass/fail summary.
• Verify that any secret rotation procedure preserved least-privilege access and did not require code changes.
• If notifications are part of the smoke path, retain a minimal record of delivery/receipt for auditability.

中文

发布一致性

• 这是一次在刷新 OpenAI/Anthropic 备用密钥后的冒烟测试，不是策略或模型发布。
• 该说明与仅审阅的月度快照流程一致，不表示生产逻辑有变更。
• 由于目标仓库是 CryptoLivePoolPipelines 而不是 HkEquitySnapshotPipelines，因此无需检查 HK 快照晋升门槛。

证据缺口

• 议题正文只说明了密钥刷新和冒烟测试意图，缺少实际执行证据。
• 缺少信息包括：测试了哪些 API 路径、是否真正验证了 fallback 行为、时间戳、日志或成功/失败工件。
• 未提供密钥轮换后的来源证明，因此无法确认是否覆盖了所有相关运行环境。

下游影响

• 如果备用密钥已正确刷新，主要下游收益是降低 API 认证失败对冒烟或近生产检查的影响。
• 由于没有明确的运行日志，无法确认依赖的自动化、告警或通知路径是否已被验证。
• 对策略内容影响较小；更主要影响的是运行可靠性和密钥轮换连续性。

操作员待办事项

• 确认冒烟测试是否产出了可核验日志或任务输出，能证明刷新后的备用凭据生效。
• 补充一份简短证据包：执行时间、环境、所测 API、通过/失败摘要。
• 检查密钥轮换流程是否保持最小权限原则，且无需代码变更。
• 若冒烟流程包含通知，保留最小化的送达/接收记录以便审计。

Anthropic Claude Review

API Monthly Review

English

Release Consistency

• The issue title ("codex smoke: refreshed api secrets") and body are consistent with each other: this is a narrow, self-declared smoke test triggered by a credential rotation event, not a strategy snapshot or promotion gate.
• The declared mode is review_only; no source-code changes are claimed or in scope. This review treats it as such.
• The repository (QuantStrategyLab/CryptoLivePoolPipelines) is not QuantStrategyLab/HkEquitySnapshotPipelines, so HK promotion-gate checks (hk_low_vol_dividend_quality, hk_shareholder_yield_quality, hk_free_cash_flow_quality) are out of scope here.
• No milestone, version tag, changelog entry, or linked PR accompanies this issue. For a credential-rotation smoke test that is accepted practice, but the absence of any artifact makes it impossible to verify the test actually ran to completion.

Evidence Gaps

• No smoke-test output is attached. There is no log, CI run link, artifact, screenshot, or structured result showing that the refreshed secrets were exercised successfully against both the OpenAI and Anthropic fallback endpoints.
• No secret-rotation checklist is referenced (e.g., which environment namespaces were updated: dev / staging / prod, Kubernetes Secrets, GitHub Actions Secrets, vault paths).
• No expiry or rotation policy is documented in the issue, making it unclear when the next rotation is expected.
• No confirmation of fallback ordering after the rotation (i.e., if the primary key fails, does the secondary key correctly activate?).
• No attestation that old secrets were revoked/invalidated after the new ones were confirmed working.

Downstream Impact

• Crypto live-pool pipelines may silently degrade if the refreshed secrets are not correctly propagated to all consumers (model-inference workers, alerting bots, strategy signal generators). A missing or malformed secret would cause API calls to fail at runtime rather than at deploy time.
• If the fallback chain is broken (e.g., Anthropic key rotated but not updated in all deployment targets), any downstream pipeline that exceeds OpenAI rate limits could experience unhandled exceptions rather than a graceful fallback.
• No strategy or model output changes are expected from a credential rotation alone; this review does not recommend any strategy parameter changes based on this single snapshot issue.

Operator Action Items

1. Attach evidence: Post the CI/smoke-test run link or log excerpt confirming both API keys returned successful responses (HTTP 200 or equivalent) in a follow-up comment on issue codex smoke: refreshed api secrets #111.
2. Confirm scope of propagation: Document which environments (dev / staging / prod) received the updated secrets and mark each as verified.
3. Verify old secret revocation: Confirm in the issue that the previous API secrets have been invalidated at the provider level (OpenAI dashboard / Anthropic console).
4. Test fallback ordering: Run (or link to an existing test) that deliberately exhausts the primary key quota to confirm the Anthropic fallback activates correctly.
5. Record rotation date and next-rotation target: Add a brief comment noting the rotation timestamp and the policy-driven next-rotation date so it can be tracked in future monthly snapshots.
6. Low-risk only: Do not promote any strategy artifact or modify pipeline configuration as part of this issue; keep this change strictly to credential hygiene.

---

中文

发布一致性

• Issue 标题（"codex smoke: refreshed api secrets"）与正文一致，属于一次因密钥轮换触发的狭义冒烟测试，并非策略快照或晋级门控。
• 声明模式为 review_only，未请求任何源代码变更，本次评审亦以此为准。
• 所属仓库为 QuantStrategyLab/CryptoLivePoolPipelines，非 QuantStrategyLab/HkEquitySnapshotPipelines，因此 HK 晋级门控检查（hk_low_vol_dividend_quality、hk_shareholder_yield_quality、hk_free_cash_flow_quality）不在本次范围之内。
• 本 Issue 未关联里程碑、版本标签、变更日志或 PR。对于密钥轮换冒烟测试而言，这尚属惯例，但缺乏任何产出物，无法核实测试是否完整执行完毕。

证据缺口

• 未附冒烟测试输出。 无日志、CI 运行链接、产出物、截图或结构化结果，无法确认刷新后的密钥已成功向 OpenAI 和 Anthropic 两个回退端点发起调用。
• 未引用密钥轮换检查清单（例如：dev / staging / prod、Kubernetes Secrets、GitHub Actions Secrets、Vault 路径等各环境命名空间是否均已更新）。
• 未记录过期或轮换策略，无法确认下一次轮换的预期时间。
• 未确认轮换后回退顺序是否正确（即主密钥失效时，备用密钥能否正确激活）。
• 未证明旧密钥已吊销/失效（即在新密钥确认可用后，旧密钥是否已在提供商侧撤销）。

下游影响

• 若刷新后的密钥未正确同步至所有消费方（模型推理 worker、告警机器人、策略信号生成器），加密实盘池流水线可能在运行时静默降级，而非在部署阶段报错。
• 若回退链路中断（例如 Anthropic 密钥已轮换，但未同步至所有部署目标），当 OpenAI 触达速率限制时，下游流水线可能抛出未处理异常，而非优雅回退。
• 密钥轮换本身不涉及策略或模型输出变更；本次评审不建议基于单一快照 Issue 对策略参数做任何调整。

操作员待办事项

1. 补充证据：在 Issue codex smoke: refreshed api secrets #111 中补充 CI / 冒烟测试运行链接或日志片段，确认两个 API 密钥均返回成功响应（HTTP 200 或等效状态码）。
2. 确认传播范围：记录哪些环境（dev / staging / prod）已完成密钥更新，并逐一标注为"已验证"。
3. 核实旧密钥吊销：在 Issue 中确认旧 API 密钥已在提供商侧（OpenAI 控制台 / Anthropic 控制台）完成撤销。
4. 测试回退顺序：运行（或链接现有测试），主动耗尽主密钥配额，验证 Anthropic 回退能否正确激活。
5. 记录轮换时间与下一次计划时间：在 Issue 中简要备注本次轮换时间戳及策略要求的下次轮换目标日期，供后续月度快照追踪使用。
6. 仅限低风险操作：本 Issue 中不得晋级任何策略产出物或修改流水线配置，严格限于密钥安全卫生范畴。

[Pigbibi]

Smoke complete: after refreshing GitHub Secrets, Codex service failure was classified as unknown and API fallback succeeded with both OpenAI and Anthropic reviewers. Evidence: https://github.com/QuantStrategyLab/CodexAuditBridge/actions/runs/28650601028