response-tone-polisher
Polishes response letters by transforming defensive or harsh language.
41
27%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Academic Writing/response-tone-polisher/SKILL.mdQuality
Discovery
32%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 identifies a reasonably specific niche—polishing response letters with defensive or harsh tone—but lacks explicit trigger guidance ('Use when...') and doesn't enumerate concrete actions beyond the general transformation. It would benefit from more natural trigger terms and a clear 'when to use' clause to help Claude select it appropriately.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks to soften, rewrite, or improve the tone of a response letter, complaint reply, or formal correspondence.'
Include more natural trigger terms users might say, such as 'soften tone', 'rewrite reply', 'professional response', 'diplomatic language', 'complaint response', or 'tone adjustment'.
List additional specific actions beyond 'transforming defensive or harsh language', such as 'replaces accusatory phrasing, restructures negative responses into constructive alternatives, and ensures a professional and empathetic tone'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (response letters) and a general action (transforming defensive or harsh language), but doesn't list multiple specific concrete actions like rewriting tone, softening refusals, restructuring paragraphs, etc. | 2 / 3 |
Completeness | Describes what it does (polishes response letters by transforming defensive/harsh language) but has no explicit 'Use when...' clause or equivalent trigger guidance, which per the rubric caps completeness at 2, and the 'what' itself is also somewhat thin, placing this at 1. | 1 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'response letters', 'defensive', 'harsh language', and 'polishes', but misses common variations users might say such as 'tone', 'soften', 'rewrite', 'professional', 'diplomatic', or 'complaint response'. | 2 / 3 |
Distinctiveness Conflict Risk | The focus on 'response letters' and 'defensive or harsh language' provides some specificity, but could overlap with general tone-editing, writing improvement, or communication skills without clearer boundaries. | 2 / 3 |
Total | 7 / 12 Passed |
Implementation
22%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill contains genuinely useful content—the tone transformation examples, defensive language patterns table, and polite academic expressions library are valuable and actionable. However, the skill is severely bloated with generic boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template, Input Validation) that add no skill-specific value and waste significant token budget. The workflow is generic rather than task-specific, and the document structure is poorly organized with sections referencing each other in circular ways.
Suggestions
Remove all generic boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template, Output Requirements, Error Handling, Input Validation) that are not specific to tone polishing—these waste ~40% of the token budget.
Restructure the workflow to be specific to tone polishing: 1) Identify defensive phrases, 2) Classify response type, 3) Apply transformations using the expression library, 4) Verify meaning preservation, 5) Output structured result.
Consolidate the useful content (transformation table, tone patterns, polite expressions) into the primary sections and remove duplicate/circular section references like 'See ## Prerequisites above' and 'See ## Overview above'.
Reorder sections logically: Overview first, then Usage Examples, then Tone Patterns/Expressions, then Input/Output format, then References—eliminating the current scattered organization.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose and bloated. Contains massive amounts of boilerplate (Risk Assessment, Security Checklist, Lifecycle Status, Evaluation Criteria, Response Template, Output Requirements) that are generic filler unrelated to the specific skill. The actual useful content (tone patterns, expression library, examples) is buried under layers of unnecessary scaffolding. Many sections reference non-existent prerequisites or repeat themselves ('See ## Overview above for related details'). | 1 / 3 |
Actionability | The defensive-to-polished transformation table and usage examples provide concrete, useful guidance. However, the Python API and CLI examples reference scripts that may not exist or work as shown, and the core skill (tone polishing) could be performed by Claude directly without any script execution. The actual transformation rules are actionable but the execution scaffolding around them is questionable. | 2 / 3 |
Workflow Clarity | The 'Workflow' section is entirely generic boilerplate ('Confirm the user objective, required inputs...') with no specific steps for tone polishing. There are no validation checkpoints specific to the task (e.g., verify meaning preservation after transformation). The quality checklist at the end is useful but disconnected from any workflow sequence. | 1 / 3 |
Progressive Disclosure | References to external files (references/polite_expressions.json, references/tone_patterns.md, references/examples/) are present and clearly signaled. However, the main document itself is a monolithic wall of text mixing useful content with extensive boilerplate, and sections are poorly ordered (Overview appears after Implementation Details, Prerequisites appears near the end despite being referenced earlier). | 2 / 3 |
Total | 6 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- aipoch/medical-research-skills
- Commit
8277276
- Reviewed
Table of Contents
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