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response-tone-polisher

Polish reviewer-response letters by softening defensive language, preserving factual meaning, and keeping responses professional, concise, and publication-appropriate.

52

Quality

60%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./scientific-skills/Academic Writing/response-tone-polisher/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 actionable with concrete CLI and Python examples and a real bundled script, but it is weighed down by extensive generic template boilerplate and redundant input/output sections. It also inlines reference-file content and cites a missing examples directory, weakening progressive disclosure.

Suggestions

Remove or consolidate the generic template sections (Output Requirements, Output Contract, Response Template, Failure/Error Handling, Risk/Security Checklists, Lifecycle Status, Evaluation Criteria) that do not add skill-specific value, to improve conciseness.

Replace the boilerplate Workflow steps with a concrete polishing sequence (e.g. classify response_type, identify defensive phrases, apply transformation from tone_patterns.md, verify position preserved via Quality Checklist) with an explicit validation checkpoint.

De-duplicate 'Polite Academic Expressions' and 'Tone Patterns Detected' by pointing to references/polite_expressions.json and references/tone_patterns.md instead of inlining them, and either create references/examples/ or remove the dangling reference.

DimensionReasoningScore

Conciseness

The body is noticeably verbose and padded with generic template boilerplate (Output Requirements, Response Template, Output Contract, Failure Handling, Error Handling, Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria) plus overlapping input/output sections ('When to Use'/'When Not to Use', 'Input Parameters'/'Required Inputs'/'Input Validation', 'Output Format'/'Output Contract'), matching 'noticeably verbose; several unnecessary explanations or padded sections'; not a 3 because the redundancy is extensive rather than incidental.

2 / 5

Actionability

Provides concrete, mostly copy-paste-ready guidance: CLI invocations ('python scripts/main.py --interactive', '--reviewer-comment', '--polish-level heavy'), a Python API example importing TonePolisher, a parameter table, and a JSON output schema, matching 'mostly executable guidance; concrete code or commands with minor gaps'; not 5 because the Python API snippet is not verified against the bundled script's actual interface.

4 / 5

Workflow Clarity

A 5-step Workflow is present but the steps are generic template language ('Confirm the user objective...', 'Return a structured result that separates assumptions, deliverables, risks...') rather than a concrete sequence for the polishing task, and there are no validation checkpoints tied to the actual transformation; a separate Quality Checklist provides implicit validation, which keeps it at 3 rather than lower.

3 / 5

Progressive Disclosure

Section structure is reasonable and real reference files (polite_expressions.json, tone_patterns.md, scripts/main.py) are signaled, but the 'Polite Academic Expressions' and 'Tone Patterns Detected' sections duplicate content that already lives in those reference files, and the References section points to a non-existent 'references/examples/' directory, matching 'some structure but could be better organized; references present but not clearly signaled; content that should be separate is inline'.

3 / 5

Total

12

/

20

Passed

Description

70%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 is specific and occupies a clear, low-conflict niche, but it lacks an explicit 'Use when...' trigger clause, which caps its completeness. Adding concrete trigger phrases and synonyms like 'rebuttal letter' would raise both completeness and trigger-term quality.

Suggestions

Append an explicit trigger clause, e.g. 'Use when drafting or revising response-to-reviewer / rebuttal letters, or when the user mentions peer review, reviewer comments, or defensive tone in academic responses.'

Add natural user-facing synonyms such as 'rebuttal letter', 'peer review', 'response to reviewers', and 'author response' to broaden trigger-term coverage.

Clarify the single most common action first ('Soften defensive language in reviewer-response letters') before listing supporting actions to sharpen specificity.

DimensionReasoningScore

Specificity

Names the domain ('reviewer-response letters') and several concrete actions ('softening defensive language, preserving factual meaning, and keeping responses professional, concise, and publication-appropriate'), with only minor coverage gaps, matching the anchor 'lists several specific actions'.

4 / 5

Completeness

It clearly states what the skill does but contains no 'Use when...' clause or equivalent explicit trigger guidance, which per the rubric caps completeness at 3 ('has a clear what but when is missing or only weakly implied').

3 / 5

Trigger Term Quality

Includes natural terms a user might say such as 'reviewer-response letters' and 'defensive language', but omits common synonyms a user would actually utter like 'rebuttal', 'peer review', or 'response to reviewers', so it falls at 'good keyword coverage; a few natural terms missing' rather than 5.

4 / 5

Distinctiveness Conflict Risk

The narrow niche of polishing peer-reviewer response letters gives it distinct triggers with minimal overlap risk against other skills, matching the 'clear niche with distinct triggers; minimal conflict risk' anchor.

5 / 5

Total

16

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

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

14

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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