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deep-analysis

个股深度分析的核心工作流。当用户要求"深度分析 / 全面分析 / 帮我看看 / 值不值得买 / DCF / 机构建模 / 首次覆盖 / 投委会备忘录"等涉及个股研究的请求时触发。覆盖 A 股、港股、美股,产出 22 维数据 + 66 位大佬量化评审 + 6 种机构级估值建模 (DCF/Comps/LBO/3-Stmt/Merger) + 7 种研究产物 (首次覆盖/财报解读/催化剂日历/投资逻辑追踪/晨报/量化筛选/行业综述) + 6 种决策方法 (IC Memo/DD/Porter/单位经济/VCP/再平衡) + 杀猪盘检测,最终生成 Bloomberg 风格 HTML 报告 + 社交分享战报。关键词:股票、个股、深度分析、估值、DCF、comps、首次覆盖、IC memo、杀猪盘、龙虎榜、akshare。

67

Quality

85%

Does it follow best practices?

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SecuritybySnyk

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The risk profile of this skill

SKILL.md
Quality
Evals
Security

Quality

Content

73%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 thorough, highly actionable operational playbook with excellent workflow sequencing and machine-enforced validation, supported by real one-level-deep reference files. Its main weakness is conciseness — heavy structural repetition across HARD-GATE blocks and re-described schemas inflate the token budget.

Suggestions

Consolidate the ~10 HARD-GATE blocks: several share identical '绝不能' boilerplate and the same banned-phrase list ('基本面良好/值得关注/估值合理'); merge the overlapping rules into a single gate table to cut repetition.

Define the agent_analysis.json schema once (in assets/data-contracts.md) and reference it instead of re-stating the field table, the full JSON example, and the completion-definition checklist in three separate places.

Trim '设计意图/用户原话' quote padding and redundant decorative emoji headers to reduce token load without losing the operational content.

DimensionReasoningScore

Conciseness

Dense and operational without explaining concepts Claude already knows, but structurally repetitive: ~10 HARD-GATE blocks share overlapping '绝不能' boilerplate and the agent_analysis.json schema is described in three+ places, so it could be noticeably tightened.

3 / 5

Actionability

Mostly executable with copy-paste-ready bash (stage1/stage2/run.py with flags), concrete Python (compute_dcf with assumptions, Playwright autofill, JSON reads), and a full agent_analysis.json example; the qualitative 'judgment' sections are advisory rather than executable, leaving minor gaps.

4 / 5

Workflow Clarity

Clear Task 1→1.5→2→3→4→5 ordering with an explicit dependency gate, machine-enforced validation (review_stage_output.py exit codes, self-review RuntimeError block), iterate-until-critical==0 feedback loop, and per-Task progress bars — matches the score-5 anchor with checkpoints and error-recovery loops.

5 / 5

Progressive Disclosure

Well-signaled one-level-deep references (task1…task5 docs, task2.5, fin-methods/README, data-contracts.md, quality-checklist.md — all verified to exist) with a clear final reference section; minor gap is that the bulk of HARD-GATE/schema detail is inlined in SKILL.md rather than pushed to references.

4 / 5

Total

16

/

20

Passed

Description

96%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 dense, well-constructed description that answers what and when with concrete capabilities and a rich set of natural trigger phrases. It is somewhat long/padded and overlaps slightly with listed related skills, but scores high across all dimensions.

DimensionReasoningScore

Specificity

Enumerates multiple concrete capabilities rather than vague language: '22 维数据 + 66 位大佬量化评审 + 6 种机构级估值建模 (DCF/Comps/LBO/3-Stmt/Merger) + 7 种研究产物 + 6 种决策方法 + 杀猪盘检测' — comprehensive coverage matching the score-5 anchor.

5 / 5

Completeness

Explicitly answers both 'what' (the enumerated data/modeling/outputs/report pipeline) and 'when' ('当用户要求…等涉及个股研究的请求时触发') with concrete trigger phrases, matching the score-5 anchor.

5 / 5

Trigger Term Quality

Includes natural user phrases ('深度分析 / 全面分析 / 帮我看看 / 值不值得买 / DCF / 机构建模 / 首次覆盖 / 投委会备忘录') plus an explicit keyword list with synonyms and ticker-style tokens (股票、个股、估值、comps、IC memo、杀猪盘、龙虎榜、akshare), giving comprehensive natural-term coverage.

5 / 5

Distinctiveness Conflict Risk

Has a clear niche (个股深度分析 with DCF/杀猪盘/龙虎榜) and distinct triggers, but bundles 杀猪盘检测 and 龙虎榜 which are listed as separate related_skills (trap-detector, lhb-analyzer), creating minor overlap risk — fits score-4 'mostly distinct' better than 5.

4 / 5

Total

19

/

20

Passed

Validation

68%

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

Validation11 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (1106 lines); consider splitting into references/ and linking

Warning

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

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

Warning

Total

11

/

16

Passed

Repository
wbh604/UZI-Skill
Reviewed

Table of Contents

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