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paper-polish

Polishes existing academic prose while preserving the author's meaning: grammar and flow repair, tone calibration against evidence strength, AI-tone removal, and Chinese-to-English rewriting at submission quality. Never fabricates data, citations, or claims, and flags any edit that could change scientific meaning. Use when the user asks to polish a draft, fix awkward wording, remove AI flavor, translate a Chinese manuscript into publishable English, or tone down overclaiming.

80

Quality

100%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is an efficient, actionable, and well-structured overview that sequences the polishing workflow with checkpoints and offloads detail to three verified one-level-deep references. It earns full marks across all four content dimensions with no meaningful weaknesses.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — it never explains concepts Claude already knows and nearly every line carries domain-specific actionable guidance, with only trivial rhetorical flourishes that serve emphasis rather than filler.

3 / 3

Actionability

Provides concrete, specific guidance throughout — explicit do/don't transformations ('suggests' into 'proves', 'carry out research on becomes study'), a sequenced polishing pass, an evidence-strength verb ladder, and a defined delivery format; code absence is appropriate for an instruction-only prose skill.

3 / 3

Workflow Clarity

The 'One polishing pass' section gives a clear 4-step sequence (Understand, Find the real problem, Edit, Account for changes) with self-check checkpoints (sentence-by-sentence meaning comparison, meaning-risk flagging) and explicit routing for out-of-scope structural problems.

3 / 3

Progressive Disclosure

A well-organized overview pushes detail into three real, one-level-deep, clearly signaled reference files (section-conventions.md, academic-phrasebank.md, ai-tone-guardrails.md), all verified to exist, with no nested reference chains.

3 / 3

Total

12

/

12

Passed

Description

100%Weight 40%Scale 1-3

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, uses natural trigger terms, explicitly states both capabilities and when to use the skill, and carves out a distinct niche with a faithfulness constraint. It uses third person throughout with no voice violations.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'grammar and flow repair', 'tone calibration against evidence strength', 'AI-tone removal', 'Chinese-to-English rewriting at submission quality', and 'flags any edit that could change scientific meaning' — matching the score-3 anchor for multiple specific concrete actions.

3 / 3

Completeness

Explicitly answers both what (the polishing actions and faithfulness constraint) and when via an explicit 'Use when...' clause listing trigger scenarios, matching the score-3 anchor.

3 / 3

Trigger Term Quality

Covers natural phrases a user would actually say — 'polish a draft', 'fix awkward wording', 'remove AI flavor', 'translate a Chinese manuscript into publishable English', 'tone down overclaiming' — giving good coverage of common variations.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (academic prose polishing with a no-fabrication, meaning-preservation constraint) and uses distinct triggers, making it unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
HKUSTDial/Supervisor-Skills
Reviewed

Table of Contents

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