Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
日本語の概要は準備中です。原文の説明を表示しています。
Database security (encryption, access control, injection prevention), data governance (lineage, quality, MDM), and compliance frameworks (GDPR, CCPA, HIPAA)
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Layered security, each layer provides independent protection:
Encrypts DB files on disk without application changes. Encrypts data pages before writing, decrypts on read into memory. AES 128/256-bit symmetric encryption. Transparent to applications.
-- SQL Server TDE (key hierarchy: Service Master Key -> DB Master Key -> Certificate -> DEK)
CREATE DATABASE ENCRYPTION KEY WITH ALGORITHM = AES_256
ENCRYPTION BY SERVER CERTIFICATE TDE_Cert;
ALTER DATABASE [YourDB] SET ENCRYPTION ON;
-- PostgreSQL: pgcrypto for column-level, full TDE in v17+ | Oracle: ALTER SYSTEM SET ENCRYPTION KEY
sslmode=require in PostgreSQL)Assign permissions to roles, roles to users. Standard in all major DBs.
-- PostgreSQL RBAC: create roles with specific grants, assign to users
CREATE ROLE app_readonly; GRANT SELECT ON ALL TABLES IN SCHEMA public TO app_readonly;
CREATE ROLE app_readwrite; GRANT SELECT, INSERT, UPDATE ON ALL TABLES IN SCHEMA public TO app_readwrite;
GRANT app_readonly TO reporting_user; GRANT app_readwrite TO application_user;
Access decisions based on attributes of user, resource, environment. More flexible than RBAC for complex scenarios (multi-tenant, data classification).
# VULNERABLE - string concatenation (SQL injection risk)
query = f"SELECT * FROM users WHERE name = '{user_input}'"
# SAFE - parameterized (all languages: Python %s, Java ?, C# @param, Node.js $1)
cursor.execute("SELECT * FROM users WHERE id = %s AND status = %s", (user_id, 'active'))
Input validation: whitelist allowed chars/formats | Stored procedures: reduce direct SQL exposure | Least privilege: no DDL for app accounts | WAF rules | Never expose DB error messages to end users
Track data from source through transformations to consumption:
Purpose: Regulatory compliance (GDPR Article 30) | Impact analysis (downstream schema change effects) | Root cause analysis (bad data origin) | Audit trails
| Dimension | Definition | Example Check |
|---|---|---|
| Accuracy | Correctly represents real-world entities | Email format validation |
| Completeness | Required fields populated | NOT NULL checks, completeness % |
| Consistency | Same data across systems agrees | Cross-system reconciliation |
| Timeliness | Current and available when needed | Freshness SLAs |
| Uniqueness | No unintended duplicates | Duplicate detection on business keys |
| Validity | Conforms to defined rules/formats | Range checks, enum validation |
Establish single source of truth for core entities (customer, product, location) | Define golden record resolution rules | Implement data stewardship roles | Use MDM platform or reference data services
Right to know (disclose collected data) | Right to delete | Right to opt-out of data sale | Non-discrimination regardless of privacy choices
PHI encryption at rest and in transit | Role-based access with minimum necessary standard | Audit all PHI access | Business associate agreements for third-party processors
3 copies of data | 2 different storage types | 1 copy offsite
Test recovery regularly (monthly minimum) | Document RTO and RPO | Encrypt backup files | Store encryption keys separately from backups
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概要と使いどころ
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
日本語の概要は準備中です。原文の説明を表示しています。
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
日本語の概要は準備中です。原文の説明を表示しています。
Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton user-centricity, priority validation, observable behavior assertions, traceability coverage, and walking skeleton boundary proof
日本語の概要は準備中です。原文の説明を表示しています。
Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement
日本語の概要は準備中です。原文の説明を表示しています。
5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance
日本語の概要は準備中です。原文の説明を表示しています。
Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.
日本語の概要は準備中です。原文の説明を表示しています。