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income-investment

AI Berkshire skill: Income Investment: Durable and Opportunistic Distribution Analysis. Source: skills/income-investment.md.

61

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./codex-skills/income-investment/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

92%

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

The content is an excellent, lean analytical workflow with strong actionability, clear sequencing, and built-in validation feedback loops; its only weakness is progressive disclosure, since the entire methodology lives in a single monolithic SKILL.md with no reference bundle to offload the detailed rubrics and sector tables.

Suggestions

Move the large sector-measures table and the 10-dimension scorecard into a references/ file (e.g. SECTOR_MEASURES.md, SCORECARD.md) and link to them one level deep to improve progressive disclosure.

Consider extracting the 18-section report format template into an assets/ template file that the workflow fills, reducing inline boilerplate.

DimensionReasoningScore

Conciseness

The body is dense and information-rich with no padding and no explaining of concepts Claude already knows (it assumes REIT/FFO/AFFO, CET1, BDC/NII), using tables efficiently; every section earns its place.

3 / 3

Actionability

Provides concrete copy-pasteable commands (financial_rigor.py, report_audit.py extract/verdict, date), an explicit input syntax, a fixed 18-section report format, exact output paths, and a precise verdict vocabulary.

3 / 3

Workflow Clarity

Steps 1-8 are clearly sequenced with explicit validation checkpoints (A/B/C evidence rating, INSUFFICIENT DATA gate, blocking gates) and a validate-fix-retry audit feedback loop, matching the checklist/feedback-loop anchor.

3 / 3

Progressive Disclosure

No bundle files exist and the ~200-line methodology is monolithic; external references to tools and sibling workflows are clearly signaled one-level-deep, but substantial content that could be split (sector table, scorecard, scenario spec) remains inline.

2 / 3

Total

11

/

12

Passed

Description

50%

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

The description is a concise niche label with provenance metadata but functions as a title rather than a capability statement: it states no concrete actions, includes no 'Use when...' trigger guidance, and omits the most common user terms like 'dividend' and 'yield'. Adding an action verb set and an explicit trigger clause would lift specificity, completeness, and trigger_term_quality together.

Suggestions

Lead with third-person action verbs, e.g. 'Evaluates a company's distributable income durability and opportunistic yield, classifies the income profile, and recommends a portfolio role.'

Append an explicit trigger clause: 'Use when analyzing dividends, yield, distribution sustainability, or income-fit for a holding.'

Drop the internal provenance metadata ('AI Berkshire skill:', 'Source: skills/income-investment.md.') from the user-facing description.

DimensionReasoningScore

Specificity

Names the domain and two analytical concepts ("Income Investment: Durable and Opportunistic Distribution Analysis") but uses no action verbs, so it reads as a title/provenance label rather than a concrete capability statement.

2 / 3

Completeness

A weak 'what' (a title-like purpose label) is present but the 'when' is entirely absent with no 'Use when...' clause, which the rubric caps at 2; it is not totally missing both.

2 / 3

Trigger Term Quality

Contains relevant keywords ("income", "distribution") but omits the most natural user terms ("dividend", "yield") and has no trigger phrasing, matching 'some relevant keywords but missing common variations.'

2 / 3

Distinctiveness Conflict Risk

The income/distribution niche is fairly specific and unlikely to conflict generically, but it lacks explicit triggers and conceptually overlaps sibling research workflows, leaving moderate routing ambiguity.

2 / 3

Total

8

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
xbtlin/ai-berkshire
Reviewed

Table of Contents

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