treeline

Treeline Money

Chat with your finances. Ask questions like "What's my net worth?", "How much did I spend on groceries?", or "Am I over budget?" and get instant answers from your own financial data.

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Quick Start

# 1. Install the CLI (OpenClaw handles this automatically)

# 2. Enable demo mode (sample data)
tl demo on

# 3. Try it out
tl status

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First Time Setup

For agents: If tl commands fail with "command not found", the CLI needs to be installed. OpenClaw handles installation automatically via the skill metadata. Start with demo mode so users can try queries immediately.

Verify the CLI is available with tl --version. Start with demo mode so users can try queries immediately.

Optional: Download the desktop app for visual exploration of your data.

Demo Mode

Demo mode loads sample data so users can try queries without connecting a bank:

tl demo on

To switch to real data later:

tl demo off

Demo data is separate from real data.

CLI Behavior Notes

• tl demo on prints a success message — if it seems to hang, wait a few seconds (first run initializes the database)
• Use tl demo status to verify demo mode is enabled
• Some commands may take a few seconds on first run due to database initialization
• If you see errors about missing tables, try tl demo on again

Connecting Real Data

When the user is ready to move beyond demo mode, direct them to set up a data source with the guides linked below.

Data source options:

• SimpleFIN ($1.50/month, US & Canada)
• Lunch Flow (~$3/month, global)
• CSV Import (free)

Setup guides: Bank Sync · CSV Import

Once set up, use tl sync to pull bank transactions or tl import to load a CSV.

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What is Treeline?

Treeline Money is a local-first personal finance app. All your data stays on your device in a local DuckDB database. No cloud accounts, no subscriptions required (sync services are optional), full SQL access to your financial data.

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Encrypted Databases

Encrypted databases work automatically when unlocked — the encryption key is stored in the OS keychain.

If you see "database is encrypted and locked" errors, tell the user to unlock it themselves before continuing:

• Open the Treeline desktop app and unlock from there, or
• Run tl encrypt unlock in their own terminal

Do not attempt to unlock the database or handle credentials. Unlocking must be done by the user directly, outside this conversation. Once unlocked, the key persists in the keychain until the user locks it.

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Response Formatting

Format all responses for mobile/chat:

• Use bullet points, not markdown tables
• Round numbers for readability ($1,234 not $1,234.56)
• Lead with the answer, details second
• Keep responses concise — chat isn't a spreadsheet
• Use line breaks to separate sections

Example good response:

Your net worth is $125k

Assets: $180k
- Retirement: $85k
- Savings: $25k
- Checking: $10k
- Home equity: $60k

Liabilities: $55k
- Mortgage: $52k
- Credit cards: $3k

Example bad response:

| Account | Type | Balance |
|---------|------|---------|
| My 401k Account | asset | 85234.56 |
...

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CLI Commands

Read commands (run freely)

These commands are read-only and safe to run autonomously:

tl status              # Quick account summary with balances
tl status --json       # Same, but JSON output

tl query "SQL" --json  # Run any SQL query (database opened in read-only mode)
tl sql "SQL" --json    # Same as tl query (alias)

tl backup list         # List available backups
tl doctor              # Check database health
tl demo status         # Check if demo mode is on/off

Note: tl query and tl sql open the database in read-only mode by default. They cannot modify data unless --allow-writes is passed (see write commands below).

Use tl status for quick balance checks — it's faster than a SQL query.

Write commands (ask the user first)

These commands modify local data. Always ask the user for confirmation before running them.

tl query "SQL" --allow-writes --json  # Run a SQL query with write access
tl sql "SQL" --allow-writes --json    # Same (alias)

tl sync                # Sync accounts/transactions from bank integrations
tl sync --dry-run      # Preview what would sync (read-only, safe to run)

tl import FILE -a ACCOUNT          # Import transactions from CSV
tl import FILE -a ACCOUNT --dry-run  # Preview import without applying (read-only, safe to run)
tl import FILE -a ACCOUNT --json   # JSON output for scripting

tl backup create       # Create a backup
tl backup restore NAME # Restore a backup

tl compact             # Compact database (reclaim space, optimize)

tl tag "groceries" --ids ID1,ID2  # Apply tags to transactions

tl demo on|off         # Toggle demo mode (sample data)

Tip: --dry-run variants are read-only and safe to run without confirmation. Use them to preview before asking the user to confirm the actual operation.

Use tl compact if the user mentions slow queries — it optimizes the database.

CSV Import Details

tl import auto-detects column mappings from CSV headers. Most bank CSVs work out of the box:

tl import bank_export.csv --account "Chase Checking"

The --account / -a flag accepts an account name (case-insensitive, substring match) or UUID.

Always preview first with --dry-run to verify columns were detected correctly:

tl import bank_export.csv -a "Checking" --dry-run --json

All import flags (all optional except --account):

Flag	Purpose	Example
--date-column	Override date column	--date-column "Post Date"
--amount-column	Override amount column	--amount-column "Amt"
--description-column	Override description column	--description-column "Memo"
--debit-column	Use debit column (instead of amount)	--debit-column "Debit"
--credit-column	Use credit column (instead of amount)	--credit-column "Credit"
--balance-column	Running balance (creates snapshots)	--balance-column "Balance"
--flip-signs	Negate amounts (credit card CSVs)	--flip-signs
--debit-negative	Negate positive debits	--debit-negative
--skip-rows N	Skip N rows before header	--skip-rows 3
--number-format	us, eu, or eu_space	--number-format eu
--profile NAME	Load a saved profile	--profile chase
--save-profile NAME	Save settings as profile	--save-profile chase
--dry-run	Preview without importing	--dry-run
--json	JSON output	--json

Common patterns for agents:

# Step 1: Find the account UUID
tl status --json

# Step 2: Preview import
tl import transactions.csv -a "550e8400-e29b-41d4-a716-446655440000" --dry-run --json

# Step 3: Execute import
tl import transactions.csv -a "550e8400-e29b-41d4-a716-446655440000" --json

Duplicate transactions are automatically detected and skipped on re-import via fingerprinting.

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User Skills

Treeline supports user-created skills for personal financial knowledge. Use tl skills list --json to discover existing skills and tl skills read <path> to read them.

Creating skills: When you learn something reusable about the user's finances — tag conventions, account meanings, tax categories, budget targets — ask if they'd like to save it as a skill for future conversations. To create one, write a SKILL.md file to ~/.treeline/skills/<name>/SKILL.md (use tl skills path to get the directory). Follow the Agent Skills standard (agentskills.io).

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Quick Reference

Net Worth

tl query "
WITH latest AS (
  SELECT DISTINCT ON (account_id) account_id, balance
  FROM sys_balance_snapshots
  ORDER BY account_id, snapshot_time DESC
)
SELECT
  SUM(CASE WHEN a.classification = 'asset' THEN s.balance ELSE 0 END) as assets,
  SUM(CASE WHEN a.classification = 'liability' THEN ABS(s.balance) ELSE 0 END) as liabilities,
  SUM(CASE WHEN a.classification = 'asset' THEN s.balance ELSE -ABS(s.balance) END) as net_worth
FROM accounts a
JOIN latest s ON a.account_id = s.account_id
" --json

Account Balances

tl query "
WITH latest AS (
  SELECT DISTINCT ON (account_id) account_id, balance
  FROM sys_balance_snapshots
  ORDER BY account_id, snapshot_time DESC
)
SELECT a.name, a.classification, a.institution_name, s.balance
FROM accounts a
JOIN latest s ON a.account_id = s.account_id
ORDER BY s.balance DESC
" --json

True Spending (Excluding Internal Moves)

Default pattern (exclude internal moves):

tl query "
SELECT SUM(ABS(amount)) as total_spent
FROM transactions
WHERE amount < 0
  AND transaction_date >= date_trunc('month', current_date)
  AND NOT (tags && ARRAY['transfer', 'savings', 'investment'])
" --json

Spending by Tag

tl query "
SELECT tags, SUM(ABS(amount)) as spent
FROM transactions
WHERE amount < 0
  AND transaction_date >= '2026-01-01' AND transaction_date < '2026-02-01'
  AND tags IS NOT NULL AND tags != '[]'
GROUP BY tags
ORDER BY spent DESC
" --json

Recent Transactions

tl query "
SELECT t.description, t.amount, t.transaction_date, a.name as account
FROM transactions t
JOIN accounts a ON t.account_id = a.account_id
ORDER BY t.transaction_date DESC
LIMIT 10
" --json

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Database Schema

Core Tables

accounts

Column	Description
account_id	UUID primary key
name	Account display name
classification	asset or liability
account_type	credit, investment, Loan, other, or null
institution_name	Bank/institution name
currency	Curren

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