
Kanchi Dividend SOP
FreeStreamline your US dividend investing process.
Free · Opens the source repo
What Kanchi Dividend SOP does
Kanchi Dividend SOP is designed for investors looking to implement a systematic approach to dividend investing based on Kanchi's 5-step methodology. This skill transforms the complexities of US dividend stock selection into a structured workflow, focusing on safety and repeatability rather than aggressive yield chasing. Users can expect to navigate through a comprehensive screening process, deep dives into stock fundamentals, and a clear entry planning framework that includes explicit invalidation conditions for each investment.
The workflow begins by defining investment mandates, helping users to outline their objectives, position limits, and the types of instruments they wish to include. After establishing these parameters, the skill assists in building an investable universe by screening stocks based on quality and yield, utilizing outputs from existing screening scripts or user-provided lists. This ensures that users have a tailored selection of stocks that meet their specific investment criteria.
Following the stock selection, the Kanchi Dividend SOP applies a series of rigorous checks including yield filters, growth assessments, and valuation analyses. Each step is designed to assess the safety and viability of potential investments, with sector-specific evaluations to ensure accuracy. The skill also facilitates the generation of one-page stock memos, providing a concise summary of each investment opportunity along with conditions for invalidation, making it easier for users to monitor their portfolios and make informed decisions.
When to use it
Use this skill when you need a systematic approach to US dividend investing, especially if you're looking for a structured screening and entry planning process.
When not to use it
This skill may not be suitable for investors seeking a more aggressive or speculative trading strategy, as it prioritizes safety and repeatability.
What you can build with it
Screening Dividend Stocks
Use the skill to screen and filter US dividend stocks based on Kanchi's safety and yield criteria, ensuring a quality investment selection.
Creating Investment Memos
Generate concise one-page memos for each stock, outlining key investment criteria and invalidation conditions for easy monitoring.
Monitoring Investment Safety
Utilize the skill's checks and balances to continuously monitor your portfolio for safety and performance, adapting your strategy as needed.
How to install Kanchi Dividend SOP
View source1. Install with the skills CLI
npx skills add tradermonty/claude-trading-skills/kanchi-dividend-sop --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by tradermontyKanchi 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:
- Output from
skills/value-dividend-screener/scripts/screen_dividend_stocks.py. - Output from
skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py. - 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):
python3 skills/kanchi-dividend-sop/scripts/build_entry_signals.py \
--tickers "JNJ,PG,KO" \
--alpha-pp 0.5 \
--yield-floor 3.0 \
--profile balanced --safety-bias medium \
--events-json reports/kanchi_events_2026-05-17.json \
--output-dir reports/
Workflow
1) Define mandate before screening
Collect and lock the parameters first:
- Objective: current cash income vs dividend growth.
- Max positions and position-size cap.
- Allowed instruments: stock only, or include REIT/BDC/ETF.
- Preferred account type context: taxable vs IRA-like accounts.
Load references/default-thresholds.md and apply baseline
settings unless the user overrides.
2) Build the investable universe
Start with a quality-biased universe:
- Core bucket: long dividend growth names (for example, Dividend Aristocrats style quality set).
- Satellite bucket: higher-yield sectors (utilities, telecom, REITs) in a separate risk bucket.
Use explicit source priority for ticker collection:
skills/value-dividend-screener/scripts/screen_dividend_stocks.pyoutput (FMP/FINVIZ).skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.pyoutput.- User-provided broker export or manual ticker list when APIs are unavailable.
Return a ticker list grouped by bucket before moving forward.
3) Apply Kanchi Step 1 (yield filter with trap flag)
Primary rule:
- Step-1 yield = the regular forward yield =
latest_declared_regular dividend × cadence-implied frequency / price(WS-1dividend_basis.py). Never useprofile.lastDividend/ TTM — it lags the latest declared raise (defect D5) and silently bundles specials (D4). - Apply the profile floor (income-now 4.0% / balanced 3.0% / growth-first 1.5%) to the regular yield only.
Trap & freshness controls (machine-emitted by dividend_basis.py):
special_dividend_flag→ exclude specials; report regular vs ttm yield.variable_policy_flag→FAIL(CALM-style; not an income base).cut_flag→FAIL;suspension_flag→FAIL.freeze_flag→HOLD-REVIEW(income cash-cow exception decided in Step 8 synthesis only if safety is clean & unblocked).- Data Freshness Gate: if the regular yield is within ±0.20pp of the
floor (
floor_borderline) and the latest declared dividend is not confirmed from an authoritative source, emitSTEP1-RECHECK— never a hard FAIL (this is the CFR D5 fix).
4) Apply Kanchi Step 2 (growth and safety) — sector-dispatched
Safety is sector-specific — a uniform GAAP/FCF triad mis-judges banks
(FCF meaningless) and regulated utilities (FCF structurally negative).
Use references/sector-step2-modules.md; the deterministic dispatch is
scripts/payout_safety.py.
- Always compute the payout triad: GAAP-EPS payout, Adjusted-EPS payout, FCF payout. The safety verdict uses Adjusted-EPS + FCF (consumer), or the sector module (bank / utility / insurer).
adjusted_eps_source = UNAVAILABLE⇒ capHOLD-REVIEW(fail-safe; never a silent PASS).- GAAP↔Adjusted EPS divergence > 25% ⇒ Step-4 one-off flag.
- A merger completed within 4 quarters presumes GAAP EPS is distorted
⇒ force the adjusted path or
HOLD-REVIEW(FITB/Comerica golden case). - Regulated utilities: negative FCF is not an auto-FAIL — judge on FFO/debt + allowed ROE + rate-case + equity-issuance risk.
When trend is mixed but not broken, classify as HOLD-REVIEW instead of
hard reject.
5) Apply Kanchi Step 3 (valuation) with US sector mapping
Use references/valuation-and-one-off-checks.md and apply
sector-specific valuation logic:
- Financials:
PER x PBRcan remain primary. - REITs: use
P/FFOorP/AFFOinstead of plainP/E. - Asset-light sectors: combine forward
P/E,P/FCF, and historical range.
Always report which valuation method was used for each ticker.
6) Apply Kanchi Step 4 (one-off event filter)
Reject or downgrade names where recent profits rely on one-time effects:
- Asset sale gains, litigation settlement, tax effect spikes.
- Margin spike unsupported by sales trend.
- Repeated "one-time/non-recurring" adjustments.
Record one-line evidence for each FAIL to keep auditability.
6b) Apply Kanchi Step 4b (forward structural-event scan)
Step 4 is backward-looking; Step 4b catches pending/recent structural
events (the MKC-Unilever miss, D3). For each surviving candidate, run a
WebSearch + issuer-IR/SEC check using the source hierarchy: issuer IR
→ SEC filing (8-K/10-Q/10-K/proxy/S-4) → exchange/company deck →
reputable wire → finance portals (secondary only). Record findings into a
curated events JSON and pass it via build_entry_signals.py --events-json.
- Only a major structural event caps the verdict to
HOLD-REVIEW(tx > 10% mcap, share issuance > 10–20%, leverage +0.5x EBITDA, control/listing/HQ change, merger-of-equals / RMT / spin-off / large asset sale, dividend/rating/leverage-policy change, sector-specific materiality, or rolling-24m cumulative M&A > 15% mcap). Minor bolt-ons are a CAUTION note only. - Pessimistic cap:
FAILED-DEGRADED/SKIPPED/NO_EVENT_FOUNDon a Step-5 TRIGGERED name ⇒HOLD-REVIEW+ T1 BLOCKED. WebSearch unavailable (web app / offline) is treated the same — never a silent skip.CLEAN_CONFIRMED(primary source checked) is stronger thanNO_EVENT_FOUND(search only).
7) Apply Kanchi Step 5 (buy on weakness with rules)
Set entry triggers mechanically:
- Yield trigger: current yield above 5y average yield + alpha (default
+0.5pp). - Valuation trigger: target multiple reached (
P/E,P/FFO, orP/FCF).
Execution pattern:
- Split orders:
40% -> 30% -> 30%. - Pre-order blockers: if a candidate has any unresolved
pre_order_blockers[](from WS-1/2/3 — variable/cut/suspension, adjusted-EPS-unavailable, GAAP/Adj divergence, bank credit, utility FFO/debt, event-scan failed/skipped, stale dividend, …) ORt1_blockedis true, the first tranche is blocked or downsized to a ≤20% tracking tranche — not 40%. - Sector cluster risk: when ≥
SECTOR_CLUSTER_WARN_COUNTsame-sector names pass (e.g. many small banks share one macro beta), emit a portfolio-levelCLUSTER-RISKwarning. - Require one-sentence sanity check before each unblocked add: "thesis intact vs structural break".
8) Produce standardized outputs
Always produce:
- Screening table with the actionable verdict tier:
CLEAN-PASS,PASS-CAUTION,CONDITIONAL-PASS,HOLD-REVIEW,STEP1-RECHECK,FAIL(synthesized byverdict.pyfrom Step 1 + Step 2 + Step 4b + blockers). Include evidence per row. - One-page stock memo (use
references/stock-note-template.md) with the per-ticker provenance block (price/dividend/payout/event sources,unresolved_blockers,evidence_refs[]). - Limit-order plan with split sizing, blocker gate, and invalidation.
- Top-level run_context (profile, yield_floor_pct, safety_bias, universe_source, excluded_asset_types) so a 3%-run result is never silently reused inside a 4%-run.
Output
Return and/or generate:
- SOP screening summary in markdown.
- Underwriting memo set based on
references/stock-note-template.md. - Optional plan artifact file generated by
skills/kanchi-dividend-sop/scripts/build_sop_plan.pyinreports/. - Optional Step 5 entry-signal artifacts generated by
skills/kanchi-dividend-sop/scripts/build_entry_signals.pyinreports/.
Cadence
Use this minimum rhythm:
- Weekly (15 min): check dividend and business-news changes only.
- Monthly (30 min): rerun screening and refresh order levels.
- Quarterly (60 min): deep safety review using latest filings/earnings.
Multi-Skill Handoff
Run this skill first, then hand off outputs:
- To
kanchi-dividend-review-monitorfor daily/weekly/quarterly anomaly detection. - To
kanchi-dividend-us-tax-accountingfor account-location and tax classification planning.
Guardrails
- Do not issue blind buy calls without Step 4, Step 4b and safety checks.
- Do not treat high yield as value before validating coverage quality.
- Use the regular forward yield for Step 1, never a special/TTM-inclusive
figure; near-floor + unconfirmed ⇒
STEP1-RECHECK, not FAIL. - A failed/skipped event scan on a TRIGGERED name ⇒
HOLD-REVIEW+ T1 blocked. Never silently skip Step 4b. - Keep assumptions explicit;
adjusted_eps/data missing ⇒ fail-safeHOLD-REVIEW, never silent PASS.
Resources
scripts/thresholds.py: single source of truth for all SOP thresholds +SCHEMA_VERSION(downstream schema-evolution guard).scripts/dividend_basis.py: WS-1 regular/special/variable/freeze/cut + Data Freshness Gate engine (pure, offline).scripts/payout_safety.py: WS-2 sector-aware GAAP/Adjusted/FCF payout triad + completed-merger linkage.scripts/event_scanner.py: WS-3 isolated forward/recent corporate-action scanner + materiality gate + pessimistic cap.scripts/verdict.py: WS-5 actionable-tier synthesis + run_context + evidence_ref helpers.scripts/build_entry_signals.py: orchestrator (Step 5 targets + WS-1/2/3/5 integration). Flags:--yield-floor,--events-json,--profile,--safety-bias,--universe-source.scripts/build_sop_plan.py: deterministic SOP plan scaffold generator.scripts/tests/test_golden_p0.py: P0 merge gate — end-to-end frozen verdicts for CALM/ORI/CMCSA/MKC/CFR/cut (run viascripts/run_all_tests.sh).references/default-thresholds.md: human-readable threshold mirror.references/sector-step2-modules.md: Step 2 safety indicators by sector.references/valuation-and-one-off-checks.md: Step 3 valuation + Step 4 one-off.references/stock-note-template.md: one-page memo + provenance block.
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