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industry-funnel

AI Berkshire skill: 行业漏斗筛选:从全市场到 3 家的价值投资精选流程. Source: skills/industry-funnel.md.

61

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./codex-skills/industry-funnel/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.

This is a highly actionable, well-sequenced instruction skill with concrete commands, thresholds, templates, and a validation feedback loop. Its main weakness is monolithic inline content with no actual bundled reference files to progressively disclose into.

Suggestions

Move the detailed per-company analysis template (第三/四步) and the four-master rubrics into a referenced file (e.g. references/analysis-templates.md) so SKILL.md stays a lean overview.

Extract the AI-research-bias checklist and the 5-hard-indicator definitions into references/ so the core funnel flow stays scannable.

Verify the referenced tools (tools/report_audit.py, tools/financial-data.md) are discoverable from the skill's own bundle or clearly documented as repo-root dependencies.

DimensionReasoningScore

Conciseness

The body is dense with operational specifics — funnel tables, hard thresholds, output templates, and bias checklists — and avoids explaining concepts Claude already knows; the only mild padding is the Codex adapter note, but overall every section earns its place.

3 / 3

Actionability

It gives executable commands (e.g. 'python3 tools/report_audit.py extract --report ...'), exact quantitative criteria (ROE > 15%, 负债率 < 60%), and ready-to-use table and report templates, making the guidance copy-paste ready.

3 / 3

Workflow Clarity

The four-layer funnel is explicitly sequenced with per-layer keep/drop rules, mandatory elimination records, and a final 数据抽检 pass/fail gate with a fix-and-re-audit feedback loop.

3 / 3

Progressive Disclosure

Sections are well organized and external targets (tools/report_audit.py, sibling skills) are named, but no bundle files exist in references/scripts/assets and the bulk of the workflow is inline rather than split into one-level-deep reference files.

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 conveys a clear, specific purpose but omits any explicit 'when to use' trigger and relies on a single action phrase. It reads more like a source-tagged title than a self-contained routing description.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when the user names an industry or investment direction and wants to screen the whole market down to a shortlist of 3 value-investing picks.'

Enumerate the concrete actions (e.g. full-market scan, 5-criteria coarse screen, per-name analysis, four-master deep-dive) instead of naming only the funnel.

Include natural trigger variations a user would actually say, such as '行业选股', 'value investing screen', or '帮我从全市场筛出 3 家'.

DimensionReasoningScore

Specificity

Names a concrete domain and a specific outcome — '行业漏斗筛选:从全市场到 3 家的价值投资精选流程' — but only sketches one funnel action rather than listing multiple specific operations, so it is not comprehensive.

2 / 3

Completeness

It states clearly what the skill does (funnel-screen a sector down to 3 picks) but provides no explicit 'Use when...' trigger, which per the guidelines caps completeness at 2.

2 / 3

Trigger Term Quality

Relevant Chinese terms like '行业漏斗筛选' and '价值投资精选' appear, but coverage is narrow and jargon-leaning with no common variations or English keywords a user would naturally say.

2 / 3

Distinctiveness Conflict Risk

The value-investing funnel niche is fairly specific, yet without explicit triggers it could still overlap with sibling investment-research skills rather than carving a clearly distinct slot.

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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