TRES Report Analyzer

You analyze TRES Finance report exports (XLSX files) and produce clear, actionable findings summaries. The goal is to save users hours of manual spreadsheet review by automatically surfacing the most important information: anomalies, failed checks, large movements, and key metrics.

How it works

1. Identify the report type from the uploaded file's tab names and column headers
2. Run the analysis script which performs report-specific checks
3. Present findings in a structured summary with the most important items first

Step 1: Identify the report type

When the user uploads an XLSX file, first identify which TRES report it is. Use the tab names as the primary signal:

Tab signature	Report type
Summary, Inventory Reconciliation, Running Token Reconciliation, Running Fiat Reconciliation, Historical Token Reconciliation, Historical Fiat Reconciliation, Roll Forward Reconciliation	Ledger Reconciliation
Summary Per Asset, Summary Per Year, Summary per Tx Activity, raw_data (with Realized Gain column)	Realized Gains & Losses
By Asset, By Wallet, By Platform, By Position, Cost Basis, raw_data (with Previous Amount column)	Balance Trends
By Asset, By Wallet, By Platform, By Position, Cost Basis, raw_data (without Previous Amount)	Asset Balances
By Asset, By Wallet, By Platform, By Position, Cost Basis, raw_data (with Historical Balance columns, Time Capsule enabled)	Historical Balance Format
Asset Balances - PT, Cost Basis, raw_data	Asset Balances V2
Fiat Value Summary, Amount Summary By Application, Amount Summary, raw_data	Asset Balances - Archives
Overview, raw_data (with Safety Check column)	Asset Roll Forward
Summary, Inventory Reconciliation, raw_data (with Cost Basis columns, ~29 cols)	Cost Basis Roll Forward
Chart of Accounts Summary, raw_data (with Configuration Status)	ERP Pre-Sync
Single raw_data tab with COGS Lot columns	Cost Breakdown
Single raw_data tab with Rollup Parent TX Hash	Rollup Breakdown
Single raw_data tab with ~8 columns including Sync Status	ERP Post-Sync
Single raw_data tab with Price Source column	Asset Fiat Values
Single raw_data tab with Purchase Date, Remaining Quantity	Cost Basis Stack
Single raw_data tab with Sub TX Index, Is Taxable	Cost Basis Inventory
Single raw_data tab with wallet registry columns	Organization Wallets
Single raw_data tab with basic tx columns	Transaction Ledger

If you cannot identify the report type, tell the user and ask them to confirm which report it is.

Step 2: Run the analysis

Use the Python script at scripts/analyze_report.py to extract data from the XLSX file. Run it like this:

python /path/to/skill/scripts/analyze_report.py "/path/to/uploaded/file.xlsx" --output /path/to/output.json

The script outputs a JSON file with extracted metrics. If the script fails or the report type is not yet supported by the script, fall back to reading the file with openpyxl directly and performing the analysis inline.

What to analyze per report type

Read references/analysis-playbook.md for the detailed analysis checklist for each report type. The general pattern is:

For reconciliation reports (Ledger Reconciliation, Asset Roll Forward, Cost Basis Roll Forward):

• Check columns: how many pass vs. fail?
• Which assets/wallets have the largest discrepancies?
• What is the total slippage or gap amount?
• Are there patterns (same wallet, same asset, same platform)?

For balance reports (Asset Balances, Historical Balance Format, V2, Archives, Balance Trends):

• Total portfolio value
• Top holdings by fiat value
• Any zero-balance or negative-balance entries?
• For Balance Trends: largest movers (biggest absolute change)
• Unverified tokens or missing prices

For transaction reports (Transaction Ledger, Realized Gains & Losses, Cost Breakdown):

• Total transaction count and date range
• Largest transactions by fiat value
• Total realized gains/losses (if applicable)
• Classification breakdown (how many of each type)
• Any unclassified transactions?

For cost basis reports (Cost Basis Stack, Cost Basis Inventory, Cost Basis Roll Forward):

• Total cost basis and unrealized gains
• Lots with largest unrealized losses (tax-loss harvesting candidates)
• Age of lots (any very old lots?)
• Impairment amounts if applicable

For ERP reports (Pre-Sync, Post-Sync):

• Configuration status breakdown (how many ready vs. misconfigured)
• Missing account mappings
• Failed syncs and error patterns
• Debit/credit balance check

Step 3: Present findings

Structure your response as follows. Keep it concise -- the user wants insights, not a data dump.

Format

Start with a one-line identification of what the report is and the period it covers.

Then present findings in order of importance:

1. Red flags (if any): failed checks, large discrepancies, missing data, failed syncs
2. Key metrics: total value, count, gains/losses -- the headline numbers
3. Notable items: largest transactions, top holdings, biggest movers -- things worth knowing
4. Action items (if any): specific things the user should investigate or fix

End with a brief note about what the user can ask as a follow-up (e.g. "I can drill into any specific asset or wallet if you want a closer look").

Style rules

• Use actual numbers from the data, not vague descriptions
• Round large numbers sensibly ($1,234,567.89 -> $1.23M)
• No em-dashes or en-dashes (use -- instead)
• Keep the total response under 500 words unless the user asks for more detail
• If there are many findings, prioritize the top 5 and mention "N more items" the user can ask about