LLMQuant Credit

SkillMonitoring & ops

Router skill for LLMQuant credit workflows. Use when the user needs issuer credit review, spread regime analysis, high-yield stress monitoring, default risk, debt maturity, or covenant context.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the LLMQuant Credit skill

What this skill tells your AI

The instructions your AI receives, as published by llmquant/skills in skills/llmquant-credit/SKILL.md and read by ahel’s review.

This category routes credit research workflows for issuer risk, spread regimes, and high-yield stress.

Routing Rules

  1. Identify issuer, ticker, bond, index, sector, maturity bucket, credit rating, and horizon.
  2. Select the closest workflow below.
  3. Open only that workflow and any referenced local resources.
  4. Use LLMQuant Data for filings, debt schedule, fundamentals, rates, spreads, ratings, equity prices, CDS, and macro context.
  5. Report filing dates, market timestamps, rating dates, observation windows, stale notices, and missing inputs.

Workflow Index

User intentWorkflow
Review an issuer's balance-sheet, cash-flow, maturity, and covenant credit risk.workflows/issuer-credit-risk-review.md
Diagnose credit-spread regime, risk appetite, and sector pressure.workflows/credit-spread-regime.md
Monitor high-yield stress, refinancing risk, fallen angels, and default pressure.workflows/high-yield-stress-monitor.md

LLMQuant Data Contract

Prefer LLMQuant Data when available. The workflows may need these data capabilities:

  • Retrieve issuer filings, financial statements, debt schedules, maturity ladders, segment exposure, and risk factors.
  • Retrieve bond, CDS, spread, rating, recovery, default, and sector credit data when available.
  • Retrieve rates, yield curves, equity prices, volatility, liquidity, macro, commodity, and FX context.
  • Retrieve ETF holdings or fund-flow data for credit ETFs and crowded exposures when available.

Fallback:

  • If bond-level, CDS, or rating data is unavailable, use filings, equity, rates, and macro evidence while naming missing credit-market inputs.
  • Do not estimate covenant headroom or default probability without required terms and market data.

Signals

GitHub stars
214
Forks
28
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
llmquant-credit
Source
github.com/llmquant/skills