xiaoman

Name: xiaoman Review
Item: xiaoman
Rating: 3.0
Author: Aaron Matthews

Skill Data & Analytics Usable

Works inClaude Code

Usable Scanned — metadata only

Enables teams to build local-first financial analytics workflows without external API dependencies, reducing data exposure risk while maintaining conversatio…

Xiaoman (小满) — a conversation-first, local-first personal finance AI agent · FastAPI + LangGraph + React · data 100% local · MIT

Ask Claude to categorize and summarize your monthly spending patterns from local transaction data.
Generate a personalized budget recommendation based on your income and expense history.
Find unusual spending spikes in your financial data to identify potential savings opportunities.

85 starsMIT (commercial OK)FreeQuick setup

Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Why it matters

Enables teams to build local-first financial analytics workflows without external API dependencies, reducing data exposure risk while maintaining conversational AI capabilities for complex finance queries.

Best for

Engineering teams building privacy-sensitive financial tools or internal analytics platforms requiring local data processing.

Works in

Claude Code Claude Cowork Claude Chat

Source

https://github.com/badhope/xiaoman

By badhope

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → Plugins → Add plugin. Search and click Install. Skills work in Claude Code only.

Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.

Command

claude plugins install badhope/xiaoman

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

After installing, paste this into Claude:

Categorize and summarize my monthly spending patterns from local transaction data

CostFree

Trust Signals Auto-scanned

Stars85Contributors3Last updated2026-10-28LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-10-29 · scanner v1

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 77 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

Things to check

Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation Scores

Evaluation

Ease of Use

3/5

Versatility

3/5

Reliability

3/5

Security

3/5

Overall score3.00 / 5.00 UsableEvaluatedOct 2026

Scored from trust signals (evidence-eval-v1): 77 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

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