kanchi-dividend-sop

kanchi-dividend-sop is a skill for Codex from tradermonty/claude-trading-skills. It costs 83 tokens per session (3,289 once invoked), scanned A, original, MIT.

A repeatable procedure for selecting and planning US dividend-stock investments using Kanchi-style rules. It covers screening candidates, checking dividend quality, adapting valuation checks by sector, and planning pullback entries.

In plain words
What is it for?
Use it to screen dividend stocks, investigate shortlisted companies, plan limit orders after price pullbacks, write investment memos, and prepare monitoring or tax-account handoffs. It expects screening results or a user-provided ticker list, and some entry scripts require FMP API access.
Why use it?
It replaces ad-hoc stock selection with a defined process that emphasizes safety, repeatability, and explicit reasons to reject an investment. It also organizes the information needed for a one-page investment memo.

Skill for Codex

Written for Codex: agents/openai.yaml present.

not rated 2.8krepo +32 today A scan Socket: passSnyk: warnSkillSpector: pass 83 tokens original MIT

Good fit Use it to screen dividend stocks, investigate shortlisted companies, plan limit orders after price pullbacks, write investment memos, and prepare monitoring or tax-account handoffs. It expects screening results or a user-provided ticker list, and some entry scripts require FMP API access.

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Install with agentmods
npx agentmods add skills/tradermonty/claude-trading-skills/kanchi-dividend-sop
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-sop
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-sop

README.md
[![agentmods](https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/kanchi-dividend-sop/github.svg)](https://agentmods.dev/skills/tradermonty/claude-trading-skills/kanchi-dividend-sop)
Your own site
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/kanchi-dividend-sop"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/kanchi-dividend-sop/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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/kanchi-dividend-sop"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/kanchi-dividend-sop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,289 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 19 May 2026
  • Snyk warn 19 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 $0.00083 $0.03289
Opus 5 $0.00042 $0.01644
Sonnet 5 $0.00017 $0.00658
Haiku 4.5 $0.00008 $0.00329

Measured 12d ago against content hash db744243980e, 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-sop 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 19 executable files (scripts/build_entry_signals.py, scripts/build_sop_plan.py, scripts/dividend_basis.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-sop/SKILL.md · 291 lines

How it starts

The opening of the file, as written. The whole thing — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kanchi Dividend Sop

Overview

Implement Kanchi's 5-step method as a deterministic workflow for US dividend investing. Prioritize safety and repeatability over aggressive yield chasing.

When to Use

Use this skill when the user needs:

  • Kanchi-style dividend stock selection adapted for US equities.
  • A repeatable screening and pullback-entry process instead of ad-hoc picks.
  • One-page underwriting memos with explicit invalidation conditions.
  • A handoff package for monitoring and tax/account-location workflows.

Prerequisites

API Key Setup

The entry signal script requires FMP API access:

export FMP_API_KEY=your_api_key_here

Input Sources

Prepare one of the following inputs before running the workflow:

  1. Output from skills/value-dividend-screener/scripts/screen_dividend_stocks.py.
  2. Output from skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py.
  3. User-provided ticker list (broker export or manual list).
Expected JSON Input Format

When using --input, provide JSON in one of these formats:

{
  "profile": "balanced",
  "candidates": [
    {"ticker": "JNJ", "bucket": "core"},
    {"ticker": "O", "bucket": "satellite"}
  ]
}

Or simplified:

{
  "tickers": ["JNJ", "PG", "KO"]
}

The optional value-dividend-screener and dividend-growth-pullback-screener handoffs use stocks[].symbol. Both build_sop_plan.py --input and build_entry_signals.py --input accept that shape directly, as well as the native candidates[].ticker and tickers[] shapes above.

For deterministic artifact generation, provide tickers to:

python3 skills/kanchi-dividend-sop/scripts/build_sop_plan.py \
  --tickers "JNJ,PG,KO" \
  --output-dir reports/

For Step 5 entry timing artifacts. --yield-floor is mandatory — it is the Step-1 yield gate; without it every row fail-safes to STEP1-RECHECK (a row can never reach a PASS tier without Step 1). Pass --profile / --safety-bias for run_context, and --events-json for the Step 4b scan (absent ⇒ every row is treated as SKIPPED and a TRIGGERED name is capped to HOLD-REVIEW — never silently clean):

Read the full file on GitHub · 291 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. 12d ago First seen · 291 lines · 83 tokens per session scan A db744243980e

Subscribe to this mod's changes

kanchi-dividend-sop is a skill published in the GitHub repository tradermonty/claude-trading-skills (2,813 stars, last pushed today), licensed MIT. It adds 83 tokens to every session and 3,289 once invoked, about $0.0004 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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