kanchi-dividend-us-tax-accounting

kanchi-dividend-us-tax-accounting is a skill for Codex from BaggaT236/AI-Trading-Skills. It costs 65 tokens per session (987 once invoked), scanned A, a copy of kanchi-dividend-us-tax-accounting, MIT.

A workflow for handling US dividend tax categories and deciding where income investments may fit between taxable accounts and tax-advantaged accounts such as IRAs. It reviews items such as qualified dividends, ordinary dividends, REIT and BDC distributions, and holding periods.

In plain words
What is it for?
Use it to review 1099-DIV information, check holding periods, assess dividend tax treatment, and compare account placement for stocks, REITs, BDCs, and MLPs.
Why use it?
It organizes tax-related holding information into an auditable planning process instead of treating every dividend the same. It helps separate classification and account-location questions, while not replacing professional tax advice.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to review 1099-DIV information, check holding periods, assess dividend tax treatment, and compare account placement for stocks, REITs, BDCs, and MLPs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/baggat236/ai-trading-skills/kanchi-dividend-us-tax-accounting
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 BaggaT236/AI-Trading-Skills --skill kanchi-dividend-us-tax-accounting
Clone the repo
git clone --depth 1 https://github.com/BaggaT236/AI-Trading-Skills

Made for: Codex.

Wrote this? Show the measurements

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README.md
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<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/kanchi-dividend-us-tax-accounting"><img src="https://agentmods.dev/badge/skills/baggat236/ai-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 987 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 95% copy Near-identical to another mod 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 $0.00987
Opus 5 $0.00032 $0.00494
Sonnet 5 $0.00013 $0.00197
Haiku 4.5 $0.00006 $0.00099

Measured 12d ago against content hash 026f8af7872a, 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 12d 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

This is a copy

95% identical to kanchi-dividend-us-tax-accounting — 22 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/kanchi-dividend-us-tax-accounting/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 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)

Expected JSON Input Format

{
  "holdings": [
    {
      "ticker": "JNJ",
      "instrument_type": "stock",
      "account_type": "taxable",
      "security_type": "common",
      "hold_days_in_window": 75
    },
    {
      "ticker": "O",
      "instrument_type": "reit",
      "account_type": "ira",
      "hold_days_in_window": 100
    }
  ]
}

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.

Read the full file on GitHub · 140 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 140 lines · 65 tokens per session scan A 026f8af7872a

Subscribe to this mod's changes

kanchi-dividend-us-tax-accounting is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 65 tokens to every session and 987 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to kanchi-dividend-us-tax-accounting, differing in 22 lines, and is treated as a copy.

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