Install
$ agentstack add skill-weklund-fiduciary-spending-audit ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Instructions
Perform a spending audit using the unified SQLite ledger.
Data source
Primary: data/finance.db (SQLite)
Analysis to perform
1. Recurring charges / Subscriptions
-- Find merchants that appear monthly with consistent amounts
SELECT description,
ROUND(AVG(amount),2) as avg_amount,
COUNT(*) as occurrences,
MIN(date) as first_seen,
MAX(date) as last_seen
FROM transactions
WHERE amount > 0 AND amount = 2
AND (MAX(date) > date('now', '-60 days'))
ORDER BY avg_amount * 12 DESC;
2. Category spending breakdown
-- Monthly spending by category
SELECT substr(date,1,7) as month,
SUM(amount) as total_spent,
COUNT(*) as txn_count
FROM transactions
WHERE amount > 0
GROUP BY month
ORDER BY month;
3. Dining & delivery analysis
-- Find all dining/delivery/coffee (common national chains + generic patterns)
SELECT date, description, amount
FROM transactions
WHERE amount > 0
AND (LOWER(description) LIKE '%restaurant%'
OR LOWER(description) LIKE '%coffee%'
OR LOWER(description) LIKE '%doordash%'
OR LOWER(description) LIKE '%uber eats%'
OR LOWER(description) LIKE '%grubhub%'
OR LOWER(description) LIKE '%chipotle%'
OR LOWER(description) LIKE '%starbucks%'
OR LOWER(description) LIKE '%mcdonald%'
OR LOWER(description) LIKE '%bar %'
OR LOWER(description) LIKE '%grill%'
OR LOWER(description) LIKE '%brewing%'
OR LOWER(description) LIKE '%tavern%'
OR LOWER(description) LIKE '%pizza%'
OR LOWER(description) LIKE '%taqueria%'
OR LOWER(description) LIKE '%sushi%'
OR LOWER(description) LIKE '%cafe%'
OR LOWER(description) LIKE '%pub %'
OR LOWER(description) LIKE '%bistro%')
ORDER BY date DESC;
Note: This query catches common patterns but will miss local restaurants. Supplement by checking the Plaid category field if available, or look at merchants with amounts in the $8-$80 range that appear on evenings/weekends.
4. High-frequency merchants
SELECT description, COUNT(*) as times, SUM(amount) as total
FROM transactions WHERE amount > 0
GROUP BY description
ORDER BY total DESC LIMIT 30;
Output format
- Subscriptions to review — list with monthly cost, annual cost, last charge date
- Category red flags — categories with unusually high spend
- Quick wins — specific, actionable cuts with estimated monthly savings
- Dining/delivery score — dining-to-grocery ratio with a recommendation
Be direct and specific. Name exact dollar amounts and merchants.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: weklund
- Source: weklund/fiduciary
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.