| name | parallax-earnings-quality |
| description | Forensic earnings quality analysis: revenue recognition patterns, accruals, quality sub-scores, manipulation risk, and hidden risk detection via Parallax MCP tools. Symbol in RIC format. NOT for general stock analysis (use /parallax-deep-dive), not for full due diligence (use /parallax-due-diligence). |
Earnings Quality Analysis
When not to use
- General stock analysis → use /parallax-deep-dive
- Full due diligence → use /parallax-due-diligence
- Quick stock check → use /parallax-should-i-buy
Gotchas
- JIT-load _parallax/parallax-conventions.md for RIC resolution, parallel execution, and fallback patterns
- get_financial_analysis (Palepu framework) is async ~2-5 min — this is the core of the forensic analysis
- Quality score of 10 doesn't mean no risk — dig into sub-components
- Cross-reference news for context on any red flags found
- Focus output on actionable risk flags, not comprehensive financial review
- JIT-load
_parallax/white-label/integration-pattern.md before the Pre-Render step. Loader call is load_visual_branding() (7-key visual subset; voice structurally excluded — branding["voice"] raises KeyError). Apply §5 (Branding Header) and §7 (About This Report) in Output Format.
Usage
/parallax-earnings-quality AAPL.O
/parallax-earnings-quality 7203.T "concerned about revenue recognition"
Workflow
Execute using mcp__claude_ai_Parallax__* tools. JIT-load _parallax/parallax-conventions.md for execution mode, RIC resolution, and fallback patterns.
Batch 0 — Tool Loading
Call ToolSearch with query "+Parallax" to load the deferred MCP tool schemas before the first mcp__claude_ai_Parallax__* call.
Batch A — Data gathering (parallel)
Fire all simultaneously:
| Tool | Parameters | Notes |
|---|
get_score_analysis | symbol | Quality score trajectory (default 52-week lookback) |
get_financials | symbol, statement="income" | Revenue/margin trends (default 4 periods) |
get_financials | symbol, statement="cash_flow" | Cash conversion (default 4 periods) |
get_financials | symbol, statement="ratios" | Accrual ratios |
get_financial_analysis | symbol | Async ~2-5 min — Palepu forensic analysis |
get_news_synthesis | symbol | Async — accounting news, auditor changes |
Batch B — AI synthesis (after Batch A)
Call get_assessment with a prompt focused on: earnings quality concerns, revenue recognition patterns, accrual anomalies, cash flow vs. earnings divergence, and any specific concerns the user raised. Feed in all findings from Batch A.
Output Format
- Risk Summary (red/yellow/green traffic light for overall earnings quality)
- Quality Score Trend (52-week trajectory with inflection points flagged)
- Forensic Findings (from Palepu analysis — accruals, revenue quality, cash conversion)
- Red Flags (specific items that warrant investigation)
- News Context (any accounting-related developments)
- AI Assessment (synthesized risk opinion)
- Recommended Actions (what to monitor, what warrants deeper investigation)
- Branding Header (only if
white_label_active AND client_name != "") — single line at the very top: **<client_name>** earnings quality review. Logo handling per integration-pattern.md §5.
- About This Report (always present): one line stating branding state per integration-pattern.md §7. If a logo was skipped, append
Logo on file: <basename> as a second About This Report line.
Pre-Render — Load white-label branding
Load _parallax/white-label/integration-pattern.md §2 and compute white_label_active + client_name per that section. Apply §5 (Branding Header) and §7 (About This Report) when composing the Output Format.
AI-interaction disclosure (required regardless of view state): Render parallax-conventions.md §9.2 immediately above the disclaimer below.
Render the standard disclaimer verbatim from parallax-conventions.md §9.1.
