aws / aws/bedrock-agentcore-sdk-python
[Enhancement] Evaluation Client: extensible hook for external reasoning verification before payment settlement
- 主要言語
- Python
- スター
- 761
- フォーク
- 147
- 平均マージ
- 1日 23時間
- マージ済み PR(30日)
- 7
説明
Following up on #393 (Evaluation Client — Lifecycle, Orchestration & Online Pipeline) — raising a specific design question before the interface solidifies.
**Context**
AgentCore Payments introduces a new failure mode that goes beyond what existing guardrails cover: a payment flow where the agent's reasoning was internally consistent but the *decision to transact* was poorly grounded. The AWS blog post acknowledged this directly under roadmap: *"stronger buyer intent verification."*
The current observability stack (logs, metrics, traces in the AgentCore console) captures *what happened* after the fact. What I'm not seeing is a hook for pre-settlement verification — a point in the execution loop where external logic can inspect the agent's reasoning trace and return a structured verdict before AgentCore finalizes the payment.
**Concrete ask**
When the Evaluation Client (#393) is designed, would it support:
1. A pre-settlement callback interface — e.g. `on_before_payment(trace, context) -> VerificationResult` — that can short-circuit the transaction if the reasoning doesn't meet a defined threshold?
2. A structured trace format that evaluation logic can consume deterministically (not just raw logs)?
3. A way to attach the verification result as metadata to the transaction record, so audit trails include both *what was paid* and *why the reasoning was considered sound*?
This pattern is especially relevant for regulated use cases (financial services, healthcare, high-stakes procurement) where "the agent decided to transact" is not sufficient — you need a provable record that the reasoning behind the decision was evaluated.
Happy to share a reference architecture sketch if it would help the design discussion — particularly around the trace-format and threshold-semantics questions.
コントリビューションガイド
調査の方向性
まず issue #393 と Evaluation Client の設計に関する議論を確認し、要求されている pre-settlement callback、構造化された trace、トランザクションメタデータを、ここで説明されている AgentCore Payments のフローと比較します。検証のためのインターフェースとセマンティクスが決まり、verdict によって settlement を防止する方法と、それが監査レコードに現れる方法まで定まれば完了です。
索引モデルが issue の本文から書いたものです。
評価
- 技術スタック
- aws, python
- 領域
- ai, backend-api-design, payments
- issue の種類
- 機能追加
- 難易度
- 5/5
- 見積もり時間
- 1週間以上
- 活発さ
- 静か
- 明瞭さ
- おおむね明確
- 初心者へのやさしさ
- 38/100