Name: wellally-tech
Rating: 44.8 (1 reviews)
Author: administrakt0r

wellally-tech

Integrate multiple digital health data sources, connect to [WellAlly.tech](https://www.wellally.tech/) knowledge base, providing data import and knowledge reference for personal health management systems.

Quality

48%

Does it follow best practices?

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Securityby

Passed

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Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/wellally-tech/SKILL.md

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

Quality

Content

42%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 skill is well-structured and covers its domain thoroughly, but it is heavily padded with non-executable pseudocode and inlined material, references bundle files that do not exist, and lacks real validation checkpoints for batch data imports.

Suggestions

Move the output-format mockups, article-recommendation mapping, FAQ, and per-source integration guides into separate reference files (which currently do not exist) and link to them one level deep, then trim the body to the essential workflow.

Replace pseudocode stubs (identifySource, searchKnowledgeBase, validateImportedData returning valid:true) with either real executable scripts in a scripts/ bundle or concise prose instructions; fix the `> 140/90` bug.

Add an enforced validation checkpoint in the import workflow that actually checks required fields/ranges and stops on failure, turning the validation step from a stub into a real feedback loop.

Dimension	Reasoning	Score
Conciseness	The ~680-line body is noticeably verbose: illustrative JS pseudocode blocks (identifySource, searchKnowledgeBase, analyzeHealthStatus), a repeated Core Features section, full output-format mockups, FAQ, extensibility, and reference-resource lists pad the context with material Claude does not need.	2 / 5
Actionability	There is some concrete, executable guidance (python import scripts, mapping_config.json example) but most code is pseudocode referencing undefined functions and non-existent files, and the threshold check `data.blood_pressure?.average > 140/90` is buggy JS division rather than real logic.	3 / 5
Workflow Clarity	Steps 1–4 are clearly sequenced with a dedicated validation substep (2.4) and an error-handling section, but the batch data-import validation is a stub that always returns valid:true rather than an enforced checkpoint, so workflow clarity is capped at 3 per the destructive/batch guideline.	3 / 5
Progressive Disclosure	Header structure is reasonable and references (knowledge-base/.md, scripts/.py) are signaled, but no bundle files exist so those references point to nothing, and large blocks (output mockups, article mapping, FAQ) that belong in separate files are inlined.	3 / 5
	Total	11 / 20 Passed

Description

53%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 is anchored to a specific platform, but it omits any 'when to use' trigger guidance and relies on generic verbs rather than the concrete user phrases and source names that populate the body.

Suggestions

Add an explicit trigger clause, e.g. 'Use when importing health data from Apple Health, Fitbit, or Oura, or when querying the WellAlly.tech knowledge base for condition-specific articles.'

Replace generic verbs ('providing data import and knowledge reference') with concrete actions ('parse Apple Health XML exports, sync Fitbit/Oura via OAuth, recommend knowledge-base articles from health data').

Include natural user phrases and source names (Apple Health/HealthKit, Fitbit, Oura Ring) so the description matches how users actually ask.

Dimension	Reasoning	Score
Specificity	Names the domain ('digital health data sources', 'WellAlly.tech knowledge base') and a few concrete actions ('Integrate', 'connect to', 'providing data import and knowledge reference'), but the actions are generic and coverage is not comprehensive — no mention of article recommendations or field mapping.	3 / 5
Completeness	Has a clear 'what' (integrate data sources, connect knowledge base, data import, knowledge reference) but no 'Use when...' clause or equivalent explicit trigger guidance, so completeness is capped at 3 per the rubric guideline.	3 / 5
Trigger Term Quality	Includes relevant terms ('digital health data sources', 'knowledge base', 'data import', 'personal health management') but misses the natural phrases and product names users actually say ('Apple Health', 'Fitbit', 'Oura', 'import my health data'), with no synonyms or file extensions.	3 / 5
Distinctiveness Conflict Risk	The explicit WellAlly.tech knowledge base tie gives it a clear niche with mostly distinct triggers; only minor overlap risk with a generic health-data skill, fitting the 'mostly distinct' anchor rather than the fully distinct one above.	4 / 5
	Total	13 / 20 Passed

Validation

81%

Warnings & errors only

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

Validation — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (687 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 5 missing	Warning

	Total	13 / 16 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/wellally-tech/SKILL.md
Commit: 900c504

Reviewed: 1 hour ago

Table of Contents

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