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management-deep-dive

AI Berkshire skill: 管理层纵深研究:买股票就是买人. Source: skills/management-deep-dive.md.

46

Quality

48%

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SecuritybySnyk

Low

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tessl review fix ./codex-skills/management-deep-dive/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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.

The body is a well-structured, actionable management-research workflow with concrete templates, thresholds, tool calls, and a clear nine-step sequence plus weighted scoring. It is somewhat padded with repeated investor aphorisms, but the core guidance is specific and usable.

DimensionReasoningScore

Conciseness

The workflow is mostly dense and actionable (table templates, thresholds, scoring rubrics), but the 设计理念 framing and repeated Buffett/Li Lu/Duan Yongping quotes across several steps add philosophical padding that could be trimmed without losing guidance.

3 / 5

Actionability

It gives concrete, executable guidance: named data sources (股东信、电话会、采访), a concrete tool call (`tools/financial_rigor.py verify-valuation`), explicit thresholds (>80% 兑现率 = 优秀), a fixed output path, and fill-in table templates; minor gaps are that most instructions are templates rather than fully specified commands.

4 / 5

Workflow Clarity

Nine clearly sequenced steps (第一步–第九步) with defined deliverables, a report structure, and a weighted scoring rubric; the adapter note supplies cross-check/validation rules, though there is no single explicit "validate data before saving" checkpoint.

4 / 5

Progressive Disclosure

No bundle files exist, but the single SKILL.md is well-organized with clear step/section headers and the one external reference (`tools/financial_rigor.py`) is clearly signaled; content is appropriately self-contained for a workflow skill, with only minor inline bulk that could optionally be split.

4 / 5

Total

15

/

20

Passed

Description

28%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.

The description functions as a domain label with a catchy tagline rather than a capability+trigger statement: it tells what topic the skill covers but not what it concretely does or when to invoke it. It is distinguishable but thin on actionable specifics and missing any "Use when" guidance.

Suggestions

Rewrite the description in third person to state concrete actions, e.g. "Evaluates company management teams by tracking CEO promise fulfillment, scoring capital allocation decisions, and assessing governance and stakeholder treatment."

Add an explicit trigger clause: "Use when assessing a company's management team, when standard investment research gives an uncertain management rating (★★★ or below), or when management is central to the investment thesis."

Drop the meta prefixes ("AI Berkshire skill:", "Source: skills/management-deep-dive.md.") from the description and keep only user-facing capability and trigger language.

DimensionReasoningScore

Specificity

The description names the domain ("管理层纵深研究:买股票就是买人") but lists no concrete actions such as evaluating CEO judgment, tracking promise fulfillment, or scoring capital allocation; it is mostly a domain label plus a tagline.

2 / 5

Completeness

It gives only a vague "what" (management in-depth research) and entirely omits "when" — there is no "Use when..." clause or equivalent trigger guidance, so it does not clear the completeness cap of 3.

2 / 5

Trigger Term Quality

It surfaces one relevant phrase ("管理层纵深研究") but lacks natural trigger variations users would say (e.g. "评估管理层", "CEO评估", "管理层分析") and offers no "Use when..." triggers; the "AI Berkshire skill:" and "Source:" prefixes are meta-noise, not user keywords.

2 / 5

Distinctiveness Conflict Risk

The management-evaluation niche is somewhat specific and the tagline is distinctive, but as a stated deep-dive variant of /investment-research it still risks overlapping with general investment-research skills.

3 / 5

Total

9

/

20

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

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