tone-adjuster

Use when converting medical text between academic and patient-friendly tones, translating medical jargon for patients, adapting research papers for public audiences, or rewriting clinical notes for patient handouts. Maintains medical accuracy while adjusting readability level.

Quality

70%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./scientific-skills/Academic Writing/tone-adjuster/SKILL.md

Quality

Content

48%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 contains genuinely useful tone-conversion guidance (rules, jargon table, best practices, pitfalls, checklist) but is weighed down by verbatim description repetition and generic boilerplate, and its code examples do not match the actual bundled script. Reference signaling and content splitting also need work.

Suggestions

Reconcile code examples with the real bundle: document scripts/main.py's actual adjust(text, tone) signature and positional CLI args, or add the convert/to_patient_friendly/assess_reading_level methods to main.py so the examples run as written.

Remove the verbatim description echoes from 'When to Use' and 'Key Features' and trim the generic boilerplate (Output Requirements, Response Template, Input Validation) to tone-adjuster-specific guidance only.

Name and link references/guidelines.md explicitly, and move the full jargon dictionary and conversion rules into a reference file rather than inlining a partial, conflicting copy.

Dimension	Reasoning	Score
Conciseness	The description is echoed verbatim in both 'When to Use' and 'Key Features', and several sections (Implementation Details, Output Requirements, Response Template, Error Handling, Input Validation) are generic boilerplate unrelated to tone adjustment, adding notable padding.	2 / 5
Actionability	Concrete code and CLI examples are present, but they reference a non-existent API (scripts/tone_adjuster.py, convert(), to_patient_friendly(), assess_reading_level(), translate_jargon()) that does not match the bundled scripts/main.py (which exposes adjust() and private helpers), so examples will not execute as written.	3 / 5
Workflow Clarity	A clear 5-step workflow with an explicit validation checkpoint (py_compile Quick Check) and a documented fallback/error path is present, though the checkpoints are generic rather than tied to verifying medical-accuracy preservation.	4 / 5
Progressive Disclosure	scripts/main.py is named and references/ is mentioned generically, but the actual references/guidelines.md is never named or linked, and an inline jargon dictionary duplicates and conflicts with the one in main.py rather than being split out.	3 / 5
	Total	12 / 20 Passed

Description

92%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, specific description that clearly answers both what the skill does and when to use it, with concrete trigger phrases and a distinct medical-tone niche. The only gap is modest synonym coverage in trigger terms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — converting tones, translating jargon, adapting research papers, rewriting clinical notes, maintaining accuracy, adjusting readability — giving comprehensive coverage of what the skill does.	5 / 5
Completeness	Explicitly states both the 'what' (convert/translate/adapt/rewrite while maintaining accuracy) and the 'when' via a concrete 'Use when converting...' trigger clause with multiple trigger scenarios.	5 / 5
Trigger Term Quality	Includes natural terms users would say ('medical jargon', 'patient-friendly', 'clinical notes', 'patient handouts', 'research papers') but omits common synonyms such as 'plain language', 'lay summary', or 'health literacy'.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear medical-tone-conversion niche with distinct triggers (academic vs patient-friendly, jargon translation), making overlap with other skills minimal.	5 / 5
	Total	19 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 2 missing	Warning

	Total	14 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Academic Writing/tone-adjuster/SKILL.md
Commit: 63c61d3

Reviewed: 5 hours ago

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