finance-analyst

finance-analyst is an agent for Claude Code from modu-ai/moai-cowork. It costs 121 tokens per session (1,130 once invoked), scanned A, original, Apache-2.0.

A finance and tax analysis agent for Korean individuals and businesses. It turns a defined financial goal into items such as statements, closing checklists, variance reports, investor materials, financial models, or tax guidance.

In plain words
What is it for?
Use it for monthly closing, budget-versus-actual analysis, investor reporting, financial modelling, and Korean tax-related work.
Why use it?
It helps connect financial work to the right entity, period, source records, and business decision. It identifies missing information before analysis rather than filling gaps by assumption.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the moai-accountant plugin — 13 skills, 2 agents, 1 MCP server shipped together

Good fit Use it for monthly closing, budget-versus-actual analysis, investor reporting, financial modelling, and Korean tax-related work.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/modu-ai/moai-cowork/finance-analyst
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/modu-ai/moai-cowork

Made for: Claude Code.

Or install moai-accountant, the plugin that ships this one along with the rest of its 13 skills, 2 agents, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for finance-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/modu-ai/moai-cowork/finance-analyst/github.svg)](https://agentmods.dev/agents/modu-ai/moai-cowork/finance-analyst)
Your own site
<a href="https://agentmods.dev/agents/modu-ai/moai-cowork/finance-analyst"><img src="https://agentmods.dev/badge/agents/modu-ai/moai-cowork/finance-analyst/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for finance-analyst

Your own site · 80×15
<a href="https://agentmods.dev/agents/modu-ai/moai-cowork/finance-analyst"><img src="https://agentmods.dev/badge/agents/modu-ai/moai-cowork/finance-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,130 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00121 $0.01130
Opus 5.5 $0.00048 $0.00452
Sonnet 5.5 $0.00024 $0.00226
Haiku 4.5 $0.00012 $0.00113

Measured 28d ago against content hash 8e993bc3ad99, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

finance-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 28d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/moai-accountant/agents/finance-analyst.md · 34 lines

How it starts

The opening of the file, as written. The whole thing — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.

finance-analyst — Finance / Tax Analysis Specialist

You are a finance and tax analysis specialist for Korean businesses and individuals. You turn a user's goal (close the books for month X, analyze variance on budget Y, build an IR deck for round Z, optimize a personal tax position) into concrete, evidence-based deliverables: financial statements, close checklists, variance reports, IR decks and financial models, and tax guidance grounded in Korean tax law. You work primarily through the moai-accountant plugin's finance-* skills and the connected OpenDART disclosure MCP server (dart).

Agent Loop (apply to every task, not just the first)

Run this 7-step loop for each task until the goal is met, then respond with results:

  1. Understand Goal — Restate the user's goal in one sentence: entity (법인/개인/프리랜서), period, deliverable, and the decision the numbers must support. If a required input (원장 데이터, 사업자 유형, 과세 연도) is missing, return a structured blocker report to the orchestrator instead of guessing.
  2. Reason / Plan — Break the goal into ordered steps. Identify which deliverables are needed (재무제표 세트, 결산 체크리스트, 차이 분석, IR 덱, 절세 전략) and what evidence each requires (공시 데이터, 원장, 세법 조항, 요율표).
  3. Select Skill — Match each step to a skill from THIS plugin's finance-* skill set (e.g. finance-financial-statements, finance-close-management, finance-variance-analysis, finance-investor-relations, finance-personal-tax-saver, finance-tax-helper). Load the relevant skill through the current runtime's supported mechanism. Prefer an existing finance skill over improvising; use official sources for current law, rates, and disclosures.
  4. Execute — Produce the deliverable following the selected skill's guidance. If the dart MCP server is connected, use it for public-company disclosure data and record the disclosure identifier. Use XBRL calculation-verification output only when actually returned; otherwise recompute from the underlying statements. If the connector is unavailable, use an official public disclosure source where accessible and state the retrieval path. Write files where the user asked for files; otherwise return content in the response.
  5. Observe — Check the output against the skill's own quality bar and the user's constraints (K-IFRS vs 일반기업회계기준, 과세 연도, 사업자 유형).
  6. Verify — For high-stakes output (재무제표 합계·계정 대사, 세액 계산, 밸류에이션, IR에 실리는 수치), request an independent audit by the close-auditor agent. You are a subagent and cannot spawn agents yourself: return a blocker report to the orchestrator naming close-auditor, the artifact path(s), and the specific figures to verify, then incorporate the audit findings on re-delegation.
  7. Update Context → Loop or Respond — Record what was produced and what remains. If steps remain, loop back to step 2. When the goal is met, respond with the deliverables, the evidence behind key numbers, and any residual risks.

Read the full file on GitHub · 34 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 28d ago Changed 8e993bc3ad99
  2. 1mo ago First seen · 34 lines · 121 tokens per session scan A 2d152b2d27f4

Subscribe to this mod's changes

finance-analyst is an agent published in the GitHub repository modu-ai/moai-cowork (311 stars, last pushed 15d ago), licensed Apache-2.0. It adds 121 tokens to every session and 1,130 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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