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kanchi-dividend-sop

Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure. Use when users ask for かんち式配当投資, dividend screening, dividend growth quality checks, PERxPBR adaptation for US sectors, pullback limit-order planning, or one-page stock memo creation. Covers screening, deep dive, entry planning, and post-purchase monitoring cadence.

69

Quality

87%

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered, highly actionable SOP: the workflow is clearly sequenced with fail-safe validation at every gate, and detail is properly pushed into real one-level-deep reference files and scripts. The main costs are unresolvable internal defect-ID references and a redundant Guardrails section, plus one dead script reference.

Suggestions

Remove or footnote the internal defect/fix references (D3, D4, D5, 'CFR D5 fix', WS-1/2/3 labels) — they reference review history no reader can resolve and spend tokens without adding guidance.

Deduplicate the Guardrails section against the body: several bullets (regular-yield rule, Step 4b pessimistic cap, fail-safe HOLD-REVIEW) restate Step 3/4b/2 rules verbatim.

Fix the dead reference: either add scripts/run_all_tests.sh or point the test_golden_p0.py invocation at a command that exists (e.g., `pytest scripts/tests/test_golden_p0.py`).

DimensionReasoningScore

Conciseness

The body is dense and assumes domain competence (no padding explaining what dividends or payout ratios are), but unresolvable internal-history tokens ("defect D5", "D4", "D3", "the CFR D5 fix") and Guardrails that largely restate body rules spend tokens a fresh reader cannot benefit from — anchor 4 (efficient with minor trimmable instances), not 5.

4 / 5

Actionability

Two complete executable commands with flags and a deterministic example (build_sop_plan.py / build_entry_signals.py invocations), concrete JSON input shapes, and hard numeric thresholds (yield floors 4.0/3.0/1.5%, +0.5pp trigger, 40%->30%->30% splits, >25% GAAP/Adjusted divergence) make most guidance copy-paste ready; minor gaps — the Step 4b WebSearch/IR check has no concrete example command, and `scripts/run_all_tests.sh` is referenced but absent from the bundle — keep it at 4 rather than 5.

4 / 5

Workflow Clarity

Steps 1–8 are explicitly sequenced with validation checkpoints throughout: the Data Freshness Gate emitting STEP1-RECHECK instead of a hard FAIL, the fail-safe "adjusted_eps_source = UNAVAILABLE ⇒ HOLD-REVIEW (never a silent PASS)", the pessimistic T1 cap on failed/skipped event scans, pre-order blocker gating of the first tranche, and the "thesis intact vs structural break" sanity check — this is the anchor 5 pattern of explicit validation and feedback loops, above anchor 4's 'most checkpoints'.

5 / 5

Progressive Disclosure

The body is a genuine overview with four one-level-deep references/ files (default-thresholds, sector-step2-modules, valuation-and-one-off-checks, stock-note-template — all verified present) each signalled at point of use, and scripts documented in a Resources section; it falls short of 5 because `scripts/run_all_tests.sh` is referenced but does not exist in the bundle and cross-skill paths point outside it.

4 / 5

Total

17

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20

Passed

Description

88%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that explicitly states what the skill does and when to use it, with concrete trigger phrases including the original Japanese term. It is specific and comprehensive, with only minor gaps: a slightly jargon-heavy trigger (PERxPBR) and a generic 'dividend screening' trigger that could collide with sibling screener skills.

DimensionReasoningScore

Specificity

"Covers screening, deep dive, entry planning, and post-purchase monitoring cadence" plus concrete actions like "PERxPBR adaptation for US sectors, pullback limit-order planning, or one-page stock memo creation" gives comprehensive, specific coverage of the whole workflow with no obvious gaps — matches the anchor 5 example's breadth, clearly above anchor 4's 'minor gaps'.

5 / 5

Completeness

Explicitly answers both: what ("Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure… Covers screening, deep dive, entry planning, and post-purchase monitoring cadence") and when ("Use when users ask for かんち式配当投資, dividend screening, …") with concrete trigger phrases — a direct match to the anchor 5 example; anchor 4 would require the 'when' to be less explicit.

5 / 5

Trigger Term Quality

Good natural keyword coverage including the source-language trigger "かんち式配当投資" alongside "dividend screening" and "one-page stock memo creation", but "PERxPBR" is jargon and common user phrasings like "dividend income" or "yield screening" are missing — fits anchor 4 (good coverage, a few natural terms missing) rather than anchor 5's synonym-and-extension completeness.

4 / 5

Distinctiveness Conflict Risk

"Kanchi-style" and "かんち式配当投資" carve a clear niche with minimal conflict risk, but the generic term "dividend screening" overlaps sibling dividend screener skills, so it sits at anchor 4 ('mostly distinct; minor overlap risk with closely related skills') rather than anchor 5.

4 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 1 missing, 1 deeper-than-1-level

Warning

Total

15

/

16

Passed

Repository
tradermonty/claude-trading-skills
Reviewed

Table of Contents

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