Cash conversion cycle, earnings quality, and working capital deep-dive
npx skills add https://github.com/openai/plugins --skill working-capital
Perform a cash conversion cycle, earnings quality, and working capital deep-dive for the company named in the user's request. If no ticker or company is provided, ask for one before proceeding.
Before starting, read ../data-access.md for data access methods and ../design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.
Follow these steps:
Look up the company by ticker using discover_companies. Capture:
company_idlatest_calendar_quarter — anchor for all period calculations below (see ../data-access.md Section 1.5)latest_fiscal_quarter../data-access.md Section 4.5Cast a wide net to discover ALL available series for this company. Search with multiple keyword sets to maximize coverage:
Collect all unique series IDs. Read every series name carefully. You need to understand:
Based on series availability, classify the business's working capital profile:
| If you find series like... | Profile | Primary focus |
|---|---|---|
| Inventory, COGS, accounts payable, accounts receivable | Inventory-intensive (manufacturing, retail, consumer goods) | Full CCC decomposition: DIO + DSO − DPO. Inventory is the core risk. Watch for inventory-to-sales divergence, channel stuffing signals, obsolescence risk |
| Deferred revenue, contract liabilities, billings, remaining performance obligations | Negative working capital / SaaS / subscription | Deferred revenue is the key asset — cash collected before revenue recognized. Focus on billings vs. revenue spread, deferred revenue growth vs. revenue growth, and whether the cash-first dynamic is strengthening or weakening |
| Receivables and payables but minimal/no inventory | Asset-light services (consulting, staffing, advertising, tech services) | DSO is the main event. Receivables quality, aging, concentration. Unbilled receivables or contract assets as early warning. DPO as a secondary lever |
| Loans, deposits, allowance for credit losses, provision expense, net charge-offs | Financial institutions (banks, specialty finance) | Traditional CCC is meaningless. Focus on provision adequacy (allowance/loans, provision/NCOs, reserve coverage), deposit cost and mix, and the gap between provision expense and actual cash losses realized as the earnings quality signal |
| Policy reserves, loss reserves, unearned premiums, LAE | Insurance | Reserve adequacy is the working capital equivalent. Prior-year reserve development (favorable/adverse), loss ratio trends, reserve-to-premium ratios. Cash flow from underwriting vs. reported underwriting income |
| Contract assets, unbilled receivables, costs to obtain contracts, progress billings | Long-cycle / contract-based (construction, defense, engineering) | Percentage-of-completion dynamics. Overbilling vs. underbilling, contract asset growth vs. revenue, cash collection timing on milestones. Watch for aggressive revenue recognition through under-reserved contract losses |
| Deferred commissions, capitalized content/software, prepaid expenses dominate | High-intangible / platform | "Hidden" working capital in capitalized costs. Focus on capitalization rate vs. amortization, whether capitalizing faster than amortizing (building a balloon), and the cash flow impact of these non-traditional working capital items |
If the company is a hybrid or doesn't map cleanly, construct a blended framework. The profile is a guide, not a constraint.
Edge cases:
Calculate 10 quarters backward from latest_calendar_quarter. Pull all working capital components identified in Step 2 for those periods:
Balance sheet (all working capital components):
Income statement:
Cash flow statement:
Important: YTD-to-quarterly conversion. Some companies (e.g., Apple) report cash flow items on a fiscal year-to-date basis rather than quarterly. Check whether CF data appears to be YTD (values increasing monotonically through the fiscal year, then resetting). If so, convert to quarterly values by subtracting the prior quarter's YTD figure. Note this conversion in the report.
Business-specific KPIs as identified in Step 2.
Derived metrics (calculate from pulled data, label each as "(calc.)" and show formulas):
Search SEC filings for context on working capital dynamics. Use profile-specific search terms:
Extract management commentary on working capital trends, collection issues, inventory management, supplier terms, etc. with document citations.
Section 1: Working Capital Profile (brief)
Section 2: Cash Conversion Cycle (or profile-adapted equivalent)
For inventory-intensive businesses, show the full CCC decomposition:
For non-inventory businesses, adapt the framework:
Section 3: Earnings Quality Assessment
This is the section that makes the report valuable for a short-seller or skeptical long. Three sub-analyses:
*3a. Accruals Analysis*
*3b. Cash Conversion Ratio*
*3c. Revenue-to-Receivables Divergence*
Section 4: Working Capital Intensity & Growth Drag
How much incremental working capital does this business consume for each dollar of revenue growth?
Section 5: Component Deep-Dives
For each material working capital component (the 2-3 that matter most for this business type), provide a focused analysis:
*Structure for each component:*
*Which components to deep-dive depends on the profile:*
Section 6: Red Flags & Green Flags
Explicit, concise checklist format. Scan the data for each of the following and report findings:
*Red flags (earnings quality / liquidity concerns):*
*Green flags (strong cash generation / conservative accounting):*
For each flag triggered, include the specific data that triggered it and the implication. Use Daloopa citations for every figure.
Section 7: Key Drivers & What to Watch
The forward-looking, analytically highest-value section:
Section 8: Summary Assessment
Analytical standards:
Use infra/chart_generator.py for charts. Include at minimum:
All charts must be embedded in the HTML as base64 data URIs (e.g., <img src="data:image/png;base64,...">) so the report is fully self-contained with no external file dependencies. After generating each chart PNG, read the file and convert to base64 for embedding. Do not use relative <img src="filename.png"> paths.
If chart_generator.py is unavailable, embed simple inline SVG charts directly in the HTML.
Save to reports/{TICKER}_working_capital.html using the HTML report template from ../design-system.md. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.
Structure the report with these sections:
<h1>{Company Name} ({TICKER}) — Working Capital & Earnings Quality Analysis</h1>
<p>Generated: {date}</p>
<h2>Summary</h2>
{2-3 sentences: What is the working capital profile? Headline finding on earnings quality. Key risk or comfort.}
<h2>Working Capital Profile</h2>
{Section 1 content}
<h2>Cash Conversion Cycle</h2>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{DSO, DIO, DPO, CCC (or profile equivalent) — with Daloopa citations and YoY change sub-rows}
</table>
{Commentary on CCC trend and any flagged moves}
<h2>Earnings Quality Assessment</h2>
<h3>Accruals Analysis</h3>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{Net Income, CFO, Accrual Ratio — with Daloopa citations}
</table>
{Decomposition of the accrual and trend analysis}
<h3>Cash Conversion Ratio</h3>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{CFO, Net Income, CFO/NI ratio, TTM CFO/NI — with Daloopa citations}
</table>
{Assessment of cash conversion quality}
<h3>Revenue vs. Receivables Divergence</h3>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{Revenue YoY growth, Receivables YoY growth, Divergence spread}
</table>
{Analysis of divergence trend}
<h2>Working Capital Intensity & Growth Drag</h2>
<table>
| Metric | Q(-9) | Q(-8) | ... | Q(latest) |
{ΔNet WC, ΔRevenue, WC Intensity Ratio, CapEx % Rev, Total Investment % Rev}
</table>
{FCF impact quantification and growth drag assessment}
<h2>Component Deep-Dives</h2>
{2-3 focused deep-dives on the most material components for this business type}
<h2>Red Flags & Green Flags</h2>
{Checklist format with specific data citations for each triggered flag}
<h2>Key Drivers & What to Watch</h2>
{Ranked drivers with scenario analysis and next-quarter monitoring items}
<h2>Summary Assessment</h2>
{3-4 sentence verdict}
All financial figures must use Daloopa citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>
Tell the user where the HTML report was saved.
Highlight the key findings: Is this a cash-generative business? Are there earnings quality concerns? What should an analyst focus on in the next filing?
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