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ai-analyzer

AI驱动的综合健康分析系统,整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

51

Quality

58%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./skills/ai-analyzer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%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 well-structured and covers a clear multi-step analysis workflow, but it suffers from cross-section redundancy, pseudocode rather than executable implementation, missing validation feedback loops, and a broken reference to a non-existent script.

Suggestions

De-duplicate the algorithm/risk-model content: describe each model once and reference it, rather than restating CUSUM/Z-score/Framingham/ADA/ASCVD in three separate sections.

Add explicit validation checkpoints to the workflow (e.g., verify each data file loaded before analysis, confirm AI is enabled before proceeding) with a fix-and-retry loop.

Resolve the broken reference to scripts/generate_ai_report.py by either providing the script in a scripts/ bundle or replacing it with inline executable report-generation guidance.

DimensionReasoningScore

Conciseness

Mostly information-dense, but the risk models and algorithm names (CUSUM, Z-score, Framingham, ADA, ASCVD) are restated across the core-features, execution-steps, and algorithm sections, and the long ✅ trigger list could be condensed.

3 / 5

Actionability

Concrete file paths and a step sequence are provided, but the code blocks use non-standard pseudocode (readFile) and the core analysis algorithms are named rather than implemented; the referenced report script does not exist.

3 / 5

Workflow Clarity

A clear numbered 9-step sequence exists with a validation check in step 1, but the batch reading of multiple data files has no further verification or feedback loops, which caps workflow clarity at 3.

3 / 5

Progressive Disclosure

Section headers give reasonable structure, but the 232-line body is monolithic with no working bundle references, and the one referenced path (scripts/generate_ai_report.py) is a broken reference since no scripts/ directory exists.

3 / 5

Total

12

/

20

Passed

Description

66%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 clearly communicates what the skill does via multiple concrete actions but omits any explicit 'when to use' trigger clause, capping completeness. Keywords are natural and the niche is reasonably distinct.

Suggestions

Add an explicit 'Use when...' clause with concrete trigger phrases (e.g., 'Use when the user asks for AI health analysis, risk prediction, or AI health report generation').

Tighten the generic opening 'integrating multi-dimensional health data' into a more concrete capability to lift specificity.

Include a couple of natural user phrasings or synonyms (e.g., '健康助手', '健康风险评估') to round out trigger term coverage.

DimensionReasoningScore

Specificity

Lists several concrete actions ("识别异常模式", "预测健康风险", "提供个性化建议", "AI健康报告生成") though the opening "整合多维度健康数据" is comparatively generic.

4 / 5

Completeness

The 'what' is clearly stated but there is no 'Use when...' clause or equivalent explicit trigger guidance, which per the rubric caps completeness at 3.

3 / 5

Trigger Term Quality

Good natural keyword coverage ("AI分析", "健康风险", "AI健康报告", "智能问答") that users would plausibly say, with a few common variations missing.

4 / 5

Distinctiveness Conflict Risk

The AI-driven comprehensive health analysis niche (prediction + reports + Q&A) is mostly distinct, with only minor overlap risk against generic health-tracking skills.

4 / 5

Total

15

/

20

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

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

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

13

/

16

Passed

Repository
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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