AgentStack
SKILL verified MIT Self-run

Spending Audit

skill-weklund-fiduciary-spending-audit · by weklund

>

No reviews yet
0 installs
11 views
0.0% view→install

Install

$ agentstack add skill-weklund-fiduciary-spending-audit

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No 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.

Are you the author of Spending Audit? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

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

  1. Subscriptions to review — list with monthly cost, annual cost, last charge date
  2. Category red flags — categories with unusually high spend
  3. Quick wins — specific, actionable cuts with estimated monthly savings
  4. 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.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet — be the first.

Versions

  • v0.1.0 Imported from the upstream source.