AgentSkillsCN

credit-analytics

债券与 CDS 利差分析、过渡行为、相对价值筛选，以及发行人层面信用信号监控的信用分析工作流。适用于在涉及利差验证、信用曲线分析、评级迁移分析，或对发行人信用状况进行生产监控的任务。

SKILL.md
--- frontmatter
name: credit-analytics
description: "Credit analytics workflows for bond and cds spread analysis, transition behavior, relative-value screening, and issuer-level credit signal monitoring. use when tasks involve spread validation, credit curve analysis, rating migration analytics, or production monitoring of issuer credit conditions."

Credit Analytics

objective

Produce actionable issuer and portfolio credit analytics using spread, curve, and migration signals.

workflow

  1. •define issuer universe, instrument mapping, and spread conventions.
  2. •construct bond, cds, and curve metrics with point-in-time consistency.
  3. •compute relative-value signals and migration-sensitive indicators.
  4. •validate signal behavior across regimes and liquidity conditions.
  5. •publish analytics only when data quality and metric stability pass controls.

required validation

  • •bond-cds basis behavior by issuer and tenor.
  • •credit spread curve slope and curvature stability.
  • •migration and downgrade risk indicators by cohort.
  • •liquidity-adjusted spread outlier detection quality.
  • •signal persistence and decay across market regimes.

risk controls

  • •enforce stale-price and illiquid-quote filters.
  • •enforce issuer and sector concentration checks in analytics outputs.
  • •enforce escalation for abrupt spread or basis discontinuities.

outputs

  • •run python scripts/credit_analytics_validation.py input.csv --output validation.json and keep the json artifact.
  • •write an implementation memo using references/credit-analytics-playbook.md with assumptions, tests, limits, and rollout plan.

resources

  • •use scripts/credit_analytics_validation.py for deterministic validation.
  • •use references/credit-analytics-playbook.md for the domain checklist and delivery structure.