Fixed income credit analysis

Invocation Protocol

When this Skill is invoked:

1. Path-sheet-driven (preferred). If the user message carries a 《工作路径单》 (work-path sheet) produced by the credit-analysis-router skill, read the engine documents in the sheet's engine_reading_order order and validate against its quality_gates.
2. Direct task, no path sheet. If the user directly names a concrete task, read the core set — dev/engine/engine-overview.md + dev/engine/dual-track-methodology.md — plus any topic-specific doc the request names (e.g. contagion-matrix.md, concentration-framework.md, lgfv-framework.md).
3. Vague / unrouted need. If the need is ambiguous and no path sheet exists, first route through the credit-analysis-router skill, or ask the Q1–Q4 questions (role / object / depth / data) yourself to pick a path from dev/engine/work-path-registry.md.
4. Use only thresholds, weights, rating mappings, and veto rules found in those documents.
5. For every quantitative judgment, cite the source document and section.
6. If a required threshold, weight, or mapping is missing from the engine documents, output 引擎未定义 and do not invent a value.
7. Do not invoke Mode B or generate external-data values unless the user has explicitly provided a CSV upload, API endpoint, or MCP server. Treat Mode B fields as data gaps until then.
8. 防漂移（结构保真）：分析维度、评分体系、分析框架一律出自引擎文档并可引用到具体章节；禁止自造维度/框架，禁止以通用信用分析先验补位（文档未定义 → 引擎未定义）。对话中间产物（调研总结、维度清单、过程评分表）同受此约束。

Fixed Income Credit Analysis Engine v0.9.6-release

Overview

A systematic methodology for evaluating corporate credit quality in China's fixed income markets. The engine operates in three layers: (1) a Mosaic Engine that assembles fragmented public data into coherent signals; (2) a Dual-Track Engine combining industry-specific multi-layer analysis pyramids with market-based pricing signals; and (3) a System-Intelligence Layer (v0.7.0-alpha) that models cross-industry contagion, portfolio concentration, and a market-wide Systemic Risk Index (SRI). Combines multi-stakeholder perspectives into a unified assessment framework.

Core principles:

1. Traditional financial analysis systematically fails in policy-driven, technology-barrier, and asset-lease industries. The heaviest credit factor is rarely on the balance sheet.
2. External credit ratings consistently lag true credit deterioration by 17+ months.
3. Mosaic theory: Individual public data fragments are meaningless alone; assembled together they form coherent signals.
4. Information completeness theory: Data gaps are not defects — they are risk signals. "We don't have this data" itself tells the user something meaningful.

When to Use

• Building an industry credit analysis framework from scratch
• Evaluating a specific company for lending or bond investment decisions
• Constructing a multi-dimensional investment dashboard (relative value + terms protection + liquidity + event calendar)
• Assembling fragmented public data into a coherent credit assessment using mosaic theory
• Retroactively validating analytical frameworks against historical defaults
• Evaluating LGFV (城投债) credit quality through the LGFV framework → read dev/engine/lgfv-framework.md
• Conducting ESG/governance risk scans and fraud detection → read dev/engine/esg-framework.md and dev/engine/governance-fraud-risk.md
• Performing LGD/recovery rate analysis for default scenarios → read dev/engine/lgd-recovery-framework.md
• Assessing external support (government, parent company) impact on creditworthiness → read dev/engine/external-support-framework.md
• Evaluating financial bonds → read dev/engine/financial-bond-framework.md
• Analyzing holding companies → read dev/engine/holding-company-framework.md
• Assessing cross-industry contagion risk from a stressed issuer or sector
• Evaluating portfolio concentration across industry, region, rating, tenor, and funding-channel dimensions
• Computing the Systemic Risk Index (SRI) and interpreting the four-level thermometer
• Mapping an industry to one of the six analytical paradigms (policy-driven, tech-barrier, consolidation, asset-lease, brand-channel, network-traffic)

Mandatory Density Rules (mandatory)

• Critical dimension signal density <20% → MUST NOT output a numeric score for that dimension; state 信息不足无法评估 and list the missing signals.
• Weighted-average density across scored dimensions <50% → MUST NOT output a final letter rating; output a qualitative directional assessment plus a prioritized gap list.
• Density 50–80% → MAY rate but MUST label 中置信度 and widen the implied interval by ±1 notch.
• The completeness report is mandatory for every analysis; omitting it is a protocol violation.

Full confidence/density model and gap-to-risk mapping: references/mosaic-engine-architecture.md (threshold single source: dev/engine/mosaic-engine.md).

Mode B: External Data Source Adapter (Placeholder)

Mode B 护栏：除非用户明确提供了 CSV 上传、API endpoint 或 MCP server，否则禁止调用 Mode B 接口，禁止生成外部数据值。在 Mode B 未激活时，所有 Mode B 字段应作为数据缺口处理。

Defined but not implemented. Adapter contract (query_bond_analytics / query_market_data / query_industry_benchmark) and connection priority (CSV > REST API > MCP > DB): dev/engine/mosaic-engine.md.

一票否决与评级上限 (Veto & Rating Ceiling — mandatory)

• 一票否决（one-shot veto）：任一分析层触发一票否决条件时，该发行人评级上限锁定为 CCC，不得上调。每层否决条件见 dev/engine/industry-framework.md §五。
• 评级映射一律采用官方 18 档表（dev/engine/dual-track-methodology.md §六）；不得自造档位。
• 城投类标的：政府信用定上限、平台自身定下限、支持意愿定落点（dev/engine/lgfv-framework.md §五）。

Two-Track Parallel Structure (Core)

Track A (fundamental, qualitative+scoring, L1 heaviest → L4 lightest) and Track B (market pricing: credit spreads / volatility / fund flows / rating migration) run in parallel, then feed a Cross-Comparison Matrix. Consensus reinforces; divergence is the most valuable insight.

When tracks diverge, prioritize Track A (auditable financial facts) over Track B (external ratings).

Full pyramid weights, Track-B thresholds, and the cross-comparison matrix: references/industry-scoring.md and dev/engine/dual-track-methodology.md.

System-Intelligence Layer (v0.7.0-alpha)

Aggregates issuer assessments into portfolio/market signals: cross-industry contagion (13×13 matrix), five-dimensional concentration, and the Systemic Risk Index SRI = Σ(industry_risk_score × industry_weight_pct) (scale 0–3+).

SRI thermometer: 🟢 normal (<0.5), 🟡 watch (0.5–1.0), 🟠 alert (1.0–1.8), 🔴 danger (≥1.8).

Full specification: references/system-intelligence.md and dev/engine/systemic-warning-framework.md.

Key Design Principles

1. Financial analysis is NEVER the heaviest layer. The heaviest factor is structural/external.
2. Each industry has a different heaviest factor determined by 10-dimension scoring.
3. Don't jump layers. L1 must pass before L2 is meaningful.
4. L4 validates, never overrules. Poor financials with strong upper layers = may be investing through cycle. Strong financials with weak upper layers = MORE dangerous (peak cycle or fraud).
5. Public data is sufficient across the 13 covered industries.
6. Track B is independent, not subordinate. Divergence generates the most valuable questions.
7. When tracks clash, prioritize auditable financial facts over external ratings.
8. Data gaps are not defects — they are risk signals. Every analysis includes a completeness report.
9. The framework identifies structural unsustainability but cannot predict default timing or specific triggers.

Chaining（链式交接）

• 上游：credit-analysis-router —— 消费其《工作路径单》（见 Invocation Protocol）。
• 产出：分析完成后输出《分析产物》（Analysis Artifact，schema 见 dev/engine/pipeline-contract.md §2.2），path_id 承自路径单。
• 下游（REQUIRED NEXT SUB-SKILL）：credit-report-builder —— 《分析产物》产出后立即自动移交该 skill 装配为交付报告；本 skill 不做报告装配。
• 交付完整性（强制）：分析完成 ≠ 交付完成。链的完成态 = 《质检裁决》产出；仅以文字性调查结论/分析摘要收尾、未产出模板报告文件，视为未完成交付（协议违规）。合法提前终止仅两种且须显式说明：① 该路径 registry templates 为 planned 标记（如实告知模板待开发）；② Mode B 数据缺口无法继续。
• 自动接续：移交 report-builder 后无需用户指令，report → qa 自动接续；不得就"是否生成报告/做成哪种形式/是否质检/是否继续"询问用户——报告模板由 registry templates 字段决定，质检是链的必经终态。全链交互点预算见 dev/engine/pipeline-contract.md §三「链式接续规则」。

References

详情已下沉至 references/（单一事实源仍为 dev/engine/ 各引擎文档）：

• references/mosaic-engine-architecture.md — 马赛克引擎 Mode A：信号置信度 / 密度评估 / Gap 映射 / 完备性输出
• references/industry-scoring.md — Track A 行业金字塔 · 六范式+LGFV · D1-D10 · C1-C4
• references/system-intelligence.md — 跨行业传染 · 五维集中度 · SRI 温度计
• references/stakeholder-paths.md — M0-M5 多视角 · M1 仪表盘 · 路径单消费指引
• dev/.claude/skills/credit-analysis-router/SKILL.md — 需求理解 / 路由层，产出《工作路径单》
• dev/engine/work-path-registry.md — 工作路径注册表（路径单一事实源）

Version History

Version	Date	Changes
0.1.0	2026-07-07	Initial release. 10-dim scoring, 4-layer pyramid, dual-track, 7 industries, solar forward-validated
0.3.0	2026-07-08	Mosaic engine architecture (Mode A+B). Multi-stakeholder coverage map. P0 bond investment dashboard. Signal confidence + density metrics. Completeness reporting. Mode B adapter interface (placeholder).
0.4.0-alpha	2026-07-08	LGD/recovery, external support, outlook/monitoring, LGFV（城投债）, ESG + governance/fraud, non-credit overlay, financial bond, holding company frameworks. Layered output. Multi-stakeholder coverage completed.
0.7.0-alpha	2026-07-13	System-intelligence layer: contagion theory/matrix, five-dimensional concentration, systemic warning (SRI), 13-industry coverage, six analytical paradigms.
0.7.1-release	2026-07-15	Dev-stack reorganization finalized; validation artifacts separated (root validation/, never in snapshots). Version headers promoted.
0.7.4	2026-07-15	SKILL.md slimmed to a navigator (≤150 lines); detail sunk to references/ (mosaic / industry / system-intelligence / stakeholder). Invocation Protocol is now path-sheet-driven (engine_reading_order). LGV→LGFV naming unified.