kanchi-dividend-us-tax-accounting

kanchi-dividend-us-tax-accounting is a skill for Codex from tradermonty/claude-trading-skills. It costs 65 tokens per session (896 once invoked), scanned A, original, MIT.

A workflow for planning how US dividend income may be taxed and where dividend-paying investments may fit across taxable and retirement accounts.

In plain words
What is it for?
Use it when reviewing qualified versus ordinary dividends, REIT or BDC distributions, holding periods, 1099-DIV details, or account-location choices.
Why use it?
It organizes checks for dividend categories, holding periods, and account placement, while making the assumptions reviewable. It is planning support, not a replacement for tax advice.

Skill for Codex

Written for Codex: agents/openai.yaml present.

not rated 2.8krepo +32 today A scan Socket: passSnyk: passSkillSpector: pass 65 tokens original MIT

Good fit Use it when reviewing qualified versus ordinary dividends, REIT or BDC distributions, holding periods, 1099-DIV details, or account-location choices.

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Install with agentmods
npx agentmods add skills/tradermonty/claude-trading-skills/kanchi-dividend-us-tax-accounting
About the project

Claude Trading Skills is a collection of Claude Code workflows for individual investors who want structured market analysis, charting, economic-calendar review, screening, trade planning, journaling, and risk management. It is designed for people using long-term investing, ETFs, dividend stocks, and disciplined swing trading, and the catalogue entries package these workflows as skills, agents, commands, settings, and instructions.

tradermonty/claude-trading-skills · 2,813 stars · on GitHub · tradermonty.github.io

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.

Any agent
npx skills add tradermonty/claude-trading-skills --skill kanchi-dividend-us-tax-accounting
Clone the repo
git clone --depth 1 https://github.com/tradermonty/claude-trading-skills

Made for: Codex.

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 kanchi-dividend-us-tax-accounting

README.md
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Your own site
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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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/kanchi-dividend-us-tax-accounting"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/kanchi-dividend-us-tax-accounting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 896 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. Third-party audits
  • Socket pass 17 May 2026
  • Snyk pass 17 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00065 $0.00896
Opus 5 $0.00032 $0.00448
Sonnet 5 $0.00013 $0.00179
Haiku 4.5 $0.00006 $0.00090

Measured 13d ago against content hash 084d3ada6b4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

kanchi-dividend-us-tax-accounting 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 13d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/build_tax_planning_sheet.py, scripts/tests/conftest.py, scripts/tests/test_build_tax_planning_sheet.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/kanchi-dividend-us-tax-accounting/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kanchi Dividend Us Tax Accounting

Overview

Apply a practical US-tax workflow for dividend investors while keeping decisions auditable. Focus on account placement and classification, not legal/tax advice replacement.

When to Use

Use this skill when the user needs:

  • US dividend tax classification planning (qualified vs ordinary assumptions).
  • Holding-period checks before year-end tax planning.
  • Account-location decisions for stock/REIT/BDC/MLP income holdings.
  • A standardized annual dividend tax memo format.

Prerequisites

Prepare holding-level inputs:

  • ticker
  • instrument_type
  • account_type
  • hold_days_in_window (if available)

Use the exact JSON contract and examples in references/input-schema.md.

For deterministic output artifacts, provide JSON input and run:

python3 skills/kanchi-dividend-us-tax-accounting/scripts/build_tax_planning_sheet.py \
  --input /path/to/tax_input.json \
  --output-dir reports/

Guardrails

Always state this clearly: tax outcomes depend on individual facts and jurisdiction. Treat this skill as planning support, then escalate final filing decisions to a tax professional.

Workflow

1) Classify each distribution stream

For each holding, classify expected cash flow into:

  • Potential qualified dividend.
  • Ordinary dividend/non-qualified distribution.
  • REIT/BDC-specific distribution components where applicable.

Use references/qualified-dividend-checklist.md for holding-period and classification checks.

2) Validate holding-period eligibility assumptions

For potential qualified treatment:

  • Check ex-dividend date windows.
  • Check required minimum holding days in the measurement window.
  • Flag positions at risk of failing holding-period requirement.

If data is incomplete, mark status as ASSUMPTION-REQUIRED.

3) Map to reporting fields

Map planning assumptions to expected tax-form buckets:

  • Ordinary dividend total.
  • Qualified dividend subset.
  • REIT-related components when reported separately.

Read the full file on GitHub · 120 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. 13d ago First seen · 120 lines · 65 tokens per session scan A 084d3ada6b4a

Subscribe to this mod's changes

kanchi-dividend-us-tax-accounting is a skill published in the GitHub repository tradermonty/claude-trading-skills (2,813 stars, last pushed today), licensed MIT. It adds 65 tokens to every session and 896 once invoked, about $0.0003 per session on Opus 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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