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goal-analyzer

分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。

53

Quality

61%

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 ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/goal-analyzer/SKILL.md

The canonical home for this skill is goal-analyzer in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

57%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 content-rich and largely actionable with concrete code, formulas, and JSON schemas, but it is verbose and monolithic — everything is inlined with no progressive disclosure to reference files and no explicit validation checkpoints in the workflow. Tightening and splitting would substantially improve it.

Suggestions

Split heavy reference material into bundle files (e.g., references/echarts-configs.md, references/achievement-catalog.md, references/smart-criteria.md) and link to them one level deep from SKILL.md to improve progressive disclosure.

Add an explicit sequenced workflow with validation checkpoints for report generation (e.g., read data → compute → validate JSON schema → write HTML → verify file) instead of presenting features as parallel sections.

Trim padded emoji bullet lists and restated concept explanations (e.g., the SMART dimension definitions) that Claude already knows, and make the validate_smart_goal snippet fully executable by defining or stubbing the helper functions.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete domain guidance (SMART thresholds, habit stages, ECharts configs), but the ~600-line body carries padded emoji bullet lists and restated concept explanations that could be tightened.

3 / 5

Actionability

Provides mostly executable guidance — ECharts configs, computation formulas like '(current_value / target_value) * 100', data file paths, and JSON output schemas — with minor gaps such as the validate_smart_goal Python snippet relying on undefined helper functions.

4 / 5

Workflow Clarity

Content is organized as eight feature sections rather than a sequenced end-to-end workflow, and the 技术实现要点 section lists steps without explicit validation checkpoints or feedback loops for the report-generation/Write operations.

3 / 5

Progressive Disclosure

Section structure is present and clear, but the body is a monolithic ~600-line SKILL.md with no bundle files (references/scripts/assets absent) and no one-level-deep references, even though content like ECharts configs and the achievement catalog clearly could be split out.

3 / 5

Total

13

/

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 states what the skill does and scopes it to a distinct health-goal niche, but it omits any explicit 'Use when...' trigger guidance, which caps completeness and limits trigger discoverability. Specificity and keyword coverage are solid but not exhaustive.

Suggestions

Add an explicit 'Use when...' clause naming concrete trigger situations (e.g., 'Use when the user sets or tracks health goals, asks about goal progress, or wants SMART validation of a fitness/nutrition/sleep target').

Broaden trigger terms with natural synonyms and file/data references users would actually say (e.g., '减重目标','习惯打卡','目标达成率','health-goals-tracker.json').

Tighten the action verbs from generic ('分析','识别') to more specific operations ('验证SMART合规性','预测完成时间','生成ECharts报告') to push specificity toward 5.

DimensionReasoningScore

Specificity

Lists several concrete actions ('分析健康目标数据、识别目标模式、评估目标进度...提供个性化目标管理建议','关联分析') scoped to a clear domain, though the verbs remain somewhat generic relative to the fully comprehensive anchor 5.

4 / 5

Completeness

The 'what' is clear (analyze goals, identify patterns, evaluate progress, give advice, correlation analysis) but there is no 'Use when...' clause or equivalent explicit trigger guidance, capping completeness at 3 per the rubric.

3 / 5

Trigger Term Quality

Good coverage of natural terms a user would mention ('健康目标','营养','运动','睡眠','目标进度'), but a few common phrasings and explicit trigger synonyms are missing.

4 / 5

Distinctiveness Conflict Risk

Scoped to health-goal management ('健康目标','目标管理'), a distinct niche with only minor overlap risk against general 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

skill_md_line_count

SKILL.md is long (608 lines); consider splitting into references/ and linking

Warning

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

Total

13

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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