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Deep-dive financial analysis — maps income and expenses, identifies savings opportunities, and creates a phased action plan with budget targets. Use when: analyze finances, financial checkup, deep dive, find savings, audit expenses, map income, understand where money goes, check financial health.
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| name | analyze |
| description | Deep-dive financial analysis — maps income and expenses, identifies savings opportunities, and creates a phased action plan with budget targets. Use when: analyze finances, financial checkup, deep dive, find savings, audit expenses, map income, understand where money goes, check financial health. |
| compatibility | Requires KolShek CLI (kolshek) installed and configured with at least one provider. |
| metadata | {"author":"kolshek","version":"0.4.8"} |
| allowed-tools | Bash Read Write AskUserQuestion |
You are performing a comprehensive financial analysis. This is a one-time (or periodic) deep dive that maps the user's entire financial picture, identifies savings opportunities, and produces an actionable plan with budget targets.
Read references/cli-reference.md for the complete command reference, DB schema, exit codes, and SQL patterns.
Run startup checks:
kolshek providers list --json — if empty, guide user to kolshek providers add.kolshek transactions list --limit 1 --json — if empty, offer to fetch.kolshek query "SELECT MAX(completed_at) as last_sync FROM sync_log WHERE status = 'success'" --json — if over 24h old, suggest kolshek fetch.Translation check: Run kolshek query "SELECT COUNT(*) as total, SUM(CASE WHEN description_en IS NOT NULL THEN 1 ELSE 0 END) as translated FROM transactions" --json. If most descriptions lack description_en, suggest running /kolshek:translate first — analysis with English descriptions is far more reliable.
Categorization check: Run kolshek query "SELECT COUNT(*) as total, SUM(CASE WHEN category IS NOT NULL AND category != '' THEN 1 ELSE 0 END) as categorized FROM transactions" --json. If most transactions are uncategorized, suggest running /kolshek:categorize first — category-based analysis requires categorized data.
Resolve config dir (needed for budget.toml later):
bun -e "import envPaths from 'env-paths'; console.log(envPaths('kolshek').config)"
Store this path — you will use it in Step 7.
Build classification exclusion list: Run kolshek categorize classify list --json to get all categories and their classifications. By default, exclude categories classified as cc_billing and transfer from expense analysis (these are internal movements, not real spending). Ask the user if they want to adjust — they may want to also exclude investment, debt, savings, or include categories that are normally excluded. Build $EXCLUDE_SQL from their choices, e.g.: category NOT IN (SELECT name FROM categories WHERE classification IN ('cc_billing', 'transfer')). If the user wants no exclusions, omit this clause entirely.
Ask the user:
Verify data coverage:
kolshek query "SELECT MIN(date) as earliest, MAX(date) as latest, COUNT(*) as total FROM transactions" --json
If data doesn't cover the requested window, warn the user and offer to fetch more: kolshek fetch --from <date> --json.
Set $FROM and $TO dates and $MONTHS count for use in subsequent steps.
Run for each month in the analysis window:
kolshek income <YYYY-MM> --json
The response includes summary.salary, summary.transfers, summary.refunds, summary.other and individual transactions with incomeType.
Also detect recurring vs one-time income sources:
kolshek query "SELECT COALESCE(t.description_en, t.description) as source, COUNT(DISTINCT strftime('%Y-%m', t.date)) as months_seen, ROUND(AVG(t.charged_amount), 2) as avg_amount, ROUND(SUM(t.charged_amount), 2) as total FROM transactions t JOIN accounts a ON t.account_id = a.id JOIN providers p ON a.provider_id = p.id WHERE t.charged_amount > 0 AND p.type = 'bank' AND t.date >= '$FROM' GROUP BY source ORDER BY total DESC" --json
Present:
Income Sources
Source Type Months Seen Avg/Month Total Salary - Acme Corp Fixed (Salary) 3/3 ₪15,000 ₪45,000 Bit Transfer - Mom One-time 1/3 ₪2,000 ₪2,000 Monthly fixed income: ₪X | Variable: ₪Y | Total avg: ₪Z
Classification rules:
kolshek income) → always FixedImportant: All subsequent calculations compare against fixed income only — never include one-time income.
Run per-month spending:
kolshek spending <YYYY-MM> --json
kolshek spending <YYYY-MM> --group-by provider --json
Run fixed vs variable analysis:
kolshek trends $MONTHS --mode fixed-variable --json
Classify each category into Mandatory or Discretionary:
fixedMerchants from trends --mode fixed-variable to identify fixed costs within each categoryPresent two tables:
Mandatory Expenses (avg/month)
Category Monthly Avg % of Income Fixed/Variable Housing ₪5,000 33% Fixed Groceries ₪2,800 19% Variable Discretionary Expenses (avg/month)
Category Monthly Avg % of Income Fixed/Variable Restaurants ₪1,200 8% Variable Entertainment ₪800 5% Variable
Present per-provider (per-card) breakdown:
Per-Card Breakdown
Provider Monthly Avg Mandatory % Discretionary % Visa Cal (personal) ₪4,500 40% 60% Leumi (joint) ₪8,000 85% 15%
Bottom line:
Fixed income: ₪X/month Total expenses: ₪Y/month (Z% mandatory, W% discretionary) Monthly surplus/deficit: ₪N
Run:
kolshek trends $MONTHS --json
kolshek insights --months $MONTHS --json
Run top 20 largest transactions (apply $EXCLUDE_SQL from Before You Start):
kolshek query "SELECT COALESCE(description_en, description) as merchant, ROUND(ABS(charged_amount), 2) as amount, date, category FROM transactions WHERE charged_amount < 0 AND $EXCLUDE_SQL AND date >= '$FROM' ORDER BY ABS(charged_amount) DESC LIMIT 20" --json
Present:
Monthly Trend
Month Income Expenses Net Savings Rate 2026-01 ₪16,000 ₪13,500 +₪2,500 15.6% 2026-02 ₪15,000 ₪12,800 +₪2,200 14.7% Top 20 Largest Transactions
# Merchant Amount Date Category 1 Rent Payment ₪5,000 2026-03-01 Housing
Flag one-time/seasonal expenses (annual insurance, holiday spending, repairs) separately — note which items in the top 20 are one-time vs recurring.
Present any alerts from kolshek insights (category spikes, new merchants, large transactions, recurring changes).
Run:
kolshek query "SELECT COALESCE(description_en, description) AS merchant, installment_number, installment_total, ROUND(ABS(charged_amount), 2) AS monthly_payment, (installment_total - installment_number) AS remaining_payments, ROUND(ABS(charged_amount) * (installment_total - installment_number), 2) AS remaining_total FROM transactions WHERE installment_total > 1 AND date >= date('now', '-30 days') ORDER BY remaining_total DESC" --json
Present:
Active Installment Plans (תשלומים)
Merchant Payment Progress Remaining Total Left IKEA ₪450/mo 3/12 9 payments ₪4,050 Monthly installment burden: ₪X Total remaining obligation: ₪Y Installments ending within 3 months: ₪Z/mo freed up
Note which installments end soon — this is "automatic" future savings.
Using all data collected above, identify savings in three tiers:
Detect recurring subscriptions:
kolshek query "SELECT COALESCE(description_en, description) AS merchant, ROUND(ABS(charged_amount), 2) AS amount, COUNT(DISTINCT strftime('%Y-%m', date)) AS months FROM transactions WHERE charged_amount < 0 AND date >= date('now', '-180 days') GROUP BY merchant, ROUND(ABS(charged_amount), 2) HAVING months >= 3 ORDER BY amount DESC" --json
Look for:
For each discretionary category, analyze spending frequency and suggest concrete targets:
Present combined savings table sorted by savings-to-effort ratio:
Savings Opportunities
# Opportunity Current Cost Monthly Saving Annual Saving Effort Priority 1 Cancel duplicate streaming ₪50/mo ₪50 ₪600 Low High 2 Reduce restaurant visits 8→4/mo ₪1,200/mo ₪600 ₪7,200 Medium High 3 Switch mobile plan ₪120/mo ₪40 ₪480 Low Medium Total potential monthly savings: ₪X Current monthly deficit: ₪Y Gap closed by savings: Z%
Always provide concrete numbers. Never give generic advice.
Ask the user:
If yes, propose targets for each spending category. Derive them from actual spending minus identified savings — targets should be challenging but realistic:
Proposed Budget Targets
Category Current Avg Proposed Target Monthly Saving Groceries ₪2,800 ₪2,500 ₪300 Restaurants ₪1,200 ₪800 ₪400 Entertainment ₪800 ₪600 ₪200 Total monthly spending target: ₪X Savings rate target: Y% of fixed income
Look good? You can adjust individual categories before I save.
After user approval, write budget.toml to the config directory (resolved in Before You Start):
# KolShek budget targets — managed by /kolshek:analyze
# Edit manually or re-run /kolshek:analyze to regenerate
[targets]
Groceries = 2500
Restaurants = 800
Entertainment = 600
# ... all categories with targets
[targets.meta]
updated = "YYYY-MM-DD"
total_spending = 12000
savings_rate_target = 20
If budget.toml already exists, show the current targets alongside proposed new ones and ask the user whether to update.
Generate a personalized plan based on the savings opportunities from Step 6:
Week 1 — Quick Wins (est. ₪X/month saved)
- Cancel [specific subscriptions] — save ₪X/month
- Call [insurance/telecom provider] for price comparison — potential ₪X/month
Month 1 — Behavioral Changes (est. ₪X/month saved)
- Restaurant budget: ₪X/month target (down from ₪Y)
- [Other category-specific targets]
Quarter 1 — Structural Changes (est. ₪X/month saved)
- Research [provider/plan switching]
- [Refinancing or other structural actions if applicable]
Total projected monthly savings: ₪X Projected savings rate after changes: Y%
Financial Health Snapshot
Metric Value Monthly fixed income ₪X Monthly expenses ₪X Current savings rate X% Mandatory vs discretionary X% / Y% Active installments ₪X/mo (₪Y remaining) Identified savings potential ₪X/mo Budget targets Set / Not set Next steps:
- Run
/kolshek:reviewmonthly to track progress against these targets- Run
/kolshek:analyzeagain in 3 months to refresh the deep dive
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