skills/capital/structuring-delayed-draw-facilities/SKILL.md
Designs delayed-draw term loan structures with commitment fees, draw conditions, and availability period mechanics. Use when structuring DDTL facilities, designing draw-down mechanisms, or analyzing delayed-draw economics.
npx skillsauth add casemark/skills structuring-delayed-draw-facilitiesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Designs delayed-draw term loan structures including commitment fee mechanics, draw-down conditions, availability periods, and economic analysis for leveraged and direct lending transactions.
Map the capital structure — Position the DDTL within the overall debt stack. Identify the initial term loan, any revolver, and where the DDTL sits in priority, maturity, and margin relative to other tranches.
Define the availability window — Specify the start date (typically closing), outside draw date, minimum/maximum draw amounts, and whether partial draws are permitted. Flag whether unused commitments terminate automatically at the outside date or require affirmative cancellation.
Structure draw conditions — Draft or review conditions precedent for each draw request:
Design fee economics — Model the commitment fee and ticking fee structure:
Address fungibility and post-draw treatment — Determine whether funded DDTL amounts are treated as a single tranche with the initial term loan for voting, amortization, prepayment waterfall, and CUSIP purposes. Specify whether the DDTL has a separate CUSIP during the availability period.
Analyze borrower cost of carry — Calculate the total cost to the borrower of maintaining the undrawn commitment versus drawing at closing, accounting for commitment fees, ticking fees, potential OID differential, and interest savings on unfunded amounts. Compare against alternative structures (e.g., an incremental facility or accordion).
Assess lender-side economics — Evaluate the yield profile for lenders holding DDTL commitments: fee income during the availability period, deployment risk, and blended yield if drawn at various points in the window.
Deliver a structured DDTL analysis containing:
development
name: automated-contract-summary language: en description: Generates structured executive summaries of contracts using ML — captures key terms, party obligations, risk allocations, and compliance requirements in a standardized format. Optimized for high-volume review where speed and consistency matter. tags: - summarization - agreement - corporate --- # Automated Contract Summarization Produces standardized executive summaries of contracts using machine learning, capturing essential term
tools
Extracts regulatory obligations from dense regulations across jurisdictions. Breaks down multi-level regulations into clear article-level obligations, classifies applicability to a business, and prioritizes by risk level. Use when translating regulations into actionable compliance requirements.
development
Continuously monitors regulatory landscapes for changes relevant to a specific business. Ingests global regulatory updates, filters by relevance, summarizes impact, and produces an actionable change advisory. Use when tracking regulatory developments affecting a particular product or market.
testing
Compares an organization's existing compliance controls, policies, and procedures against extracted regulatory obligations to identify coverage gaps. Produces a remediation plan with prioritized actions. Use when assessing compliance maturity or preparing for regulatory audits.