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stock-analysis

财务和投资分析师在进行个股研究时,当需要深度研判买卖点与趋势,使用本技能可实时获取行情,计算MACD/RSI等技术指标,精准识别缺口与支撑压力位,智能预测未来3天走势并输出专业操作建议,大幅提升投研决策效率。

61

Quality

73%

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 ./skills/stock-analysis/stock-analysis/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.

A well-structured, actionable skill body with a clear sequenced workflow and properly signaled, real one-level-deep bundle references. The main quality drag is redundancy: gap-analysis semantics repeated across three sections, duplicated dependency listings, and inline trading-concept explanations that should be consolidated or moved to a reference file.

Suggestions

State the gap-support/gap-resistance heuristics once (in step 4 or a short reference note) and delete the near-duplicate restatements in step 6 and 注意事项.

Drop the 前置准备 dependency block since it duplicates the frontmatter dependency declaration verbatim.

Add an explicit error-recovery step to the workflow for failed data fetches (e.g. 'if fetch fails, retry with an alternate code format per references/stock_code_format.md') and specify the output data-file naming convention.

DimensionReasoningScore

Conciseness

The body is mostly efficient but noticeably loose: gap-support semantics ('向上缺口:通常构成支撑位' / '向下缺口:通常构成压力位') are repeated in step 4, step 6, and the 注意事项 section; the dependency list is duplicated between frontmatter and 前置准备; and it teaches standard trading concepts Claude already knows. It fits anchor 3 ('could be tightened') better than anchor 4, since the repetition spans three separate sections.

3 / 5

Actionability

Concrete, near-executable guidance: named scripts with parameters ('调用 scripts/fetch_stock_data.py --stock_code <code> --days 30', 'analyze_stock.py --data_file <path>') plus three worked examples (000001, 00700.HK, AAPL). Minor gaps keep it at 4 rather than 5: the exact data-file naming convention is never specified and no expected output format is given for either script.

4 / 5

Workflow Clarity

A clear six-step sequence (validate code → fetch data → compute indicators → analyze → predict → recommend) with a validation checkpoint at step 1 ('确保代码格式正确'). It misses anchor 5 because there is no error-recovery feedback loop in the body — e.g. what to do when data fetch fails (that guidance exists only in references/stock_code_format.md, not the workflow itself) — which fits anchor 4 ('minor validation gaps').

4 / 5

Progressive Disclosure

Good structure with a 资源索引 section that clearly signals each real bundle file with its purpose ('获取数据…见 scripts/fetch_stock_data.py', '代码格式…见 references/stock_code_format.md'), all one level deep and verified to exist. It falls short of anchor 5 because detail material that belongs in a reference — the repeated gap-analysis heuristics in 注意事项 and the multi-bullet analysis methodology in step 4 — is inlined in SKILL.md rather than split out.

4 / 5

Total

15

/

20

Passed

Description

78%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, capability-dense description that clearly states what the skill does and when to use it, with a distinct technical-analysis niche. Its main weaknesses are light marketing fluff ('精准', '智能', '大幅提升...效率') and a 'when' clause framed around the analyst role rather than natural user requests.

Suggestions

Remove the efficiency-claim tail ('大幅提升投研决策效率') and buzzword qualifiers ('精准', '智能') — they add over-claim without aiding trigger matching.

Reframe the trigger clause around what a user would actually say, e.g. '当用户要求分析股票走势、预测涨跌或给出买卖建议时使用'.

Add one or two common natural phrasings such as 'K线' or '分析股票' to broaden trigger term coverage.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — '实时获取行情', '计算MACD/RSI等技术指标', '精准识别缺口与支撑压力位', '智能预测未来3天走势并输出专业操作建议' — which is anchor-5-level coverage, but the marketing tail '大幅提升投研决策效率' and the buzzword qualifiers '精准'/'智能' add over-claim padding that keeps it below a clean 5.

4 / 5

Completeness

Both 'what' and 'when' are explicitly present: the what is the enumerated capability chain (fetch quotes → compute indicators → identify gaps/S&R → predict → advise), and the when is '在进行个股研究时,当需要深度研判买卖点与趋势'. The trigger clause is role-framed rather than a plain 'Use when the user asks to analyze a stock' formulation, so it could be more explicit — matching anchor 4, not 5.

4 / 5

Trigger Term Quality

Good coverage of natural domain terms users would say: '个股研究', '买卖点', '趋势', '行情', 'MACD', 'RSI', '支撑压力位', '操作建议'. A few common phrasings are missing (e.g. '分析股票', 'K线', '看盘'), so it sits between anchors 4 and 5 rather than clearly at 5.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (single-stock technical analysis with MACD/RSI, gaps, support/resistance) with triggers like '买卖点' and '支撑压力位' that no adjacent skill would claim, matching the anchor-5 example of a distinct trigger set with minimal conflict risk.

5 / 5

Total

17

/

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
anbeime/skill
Reviewed

Table of Contents

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