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genai-disclaimer

Standard disclaimer and attribution templates for AI-generated or AI-assisted data analysis outputs

61

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./.claude/skills/skills/genai-disclaimer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

The body is a well-organized, highly actionable reference: ready-to-use templates plus decision tables that map output types and commands to the correct disclaimer level. Its only weakness is mild redundancy between the Full template and the attribution table.

DimensionReasoningScore

Conciseness

The body is mostly efficient (templates and decision tables rather than padding), but the Full template and the "What to Attribute to AI vs. qsv" table overlap substantially, and the Regulatory Considerations prose could be tightened, matching the level-2 anchor of mostly efficient with some redundancy.

2 / 3

Actionability

It provides copy-paste-ready Short/Medium/Full disclaimer templates, a level-selection decision table, an attribution/reproducibility matrix, and per-command integration guidance — concrete, executable material rather than vague direction.

3 / 3

Workflow Clarity

For a reference/template skill the "flow" is selection-and-apply: the "Choosing the Right Level" table plus the "Integration with Commands" list give an unambiguous path from output type to the right disclaimer, with no destructive/batch operation needing a validation loop.

3 / 3

Progressive Disclosure

The skill is self-contained with no bundle files and is organized into clearly delimited sections (When to Apply, Templates, Choosing the Right Level, Attribution, Integration, Regulatory), giving easy navigation without nested references.

3 / 3

Total

11

/

12

Passed

Description

57%

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 well-targeted to a distinctive niche and conveys what the skill produces, but it omits an explicit "Use when..." trigger and does not enumerate concrete actions, which caps specificity and completeness at 2.

Suggestions

Add an explicit trigger clause, e.g. "Use when producing AI-generated or AI-assisted data analysis outputs that require a disclaimer or attribution notice."

Name the concrete actions the skill performs (e.g. "provides short, medium, and full disclaimer templates and an attribution table"), not just the output types.

Broaden trigger terms to include natural user phrasings like "AI disclosure", "citation", or "responsible AI notice".

DimensionReasoningScore

Specificity

"Standard disclaimer and attribution templates for AI-generated or AI-assisted data analysis outputs" names a clear domain and two output types (disclaimer templates, attribution templates), but does not enumerate multiple concrete actions the skill performs, stopping short of the level-3 anchor's list of specific actions.

2 / 3

Completeness

It answers "what" clearly, but provides no explicit "Use when..." trigger clause spelling out when Claude should apply it; per the guidelines a missing explicit trigger caps completeness at 2.

2 / 3

Trigger Term Quality

It surfaces relevant natural terms users might say ("disclaimer", "attribution", "AI-generated", "data analysis"), but lacks common variations a user might actually voice (e.g. "AI disclosure", "citation", "footnote", "responsible AI notice"), so coverage is partial rather than comprehensive.

2 / 3

Distinctiveness Conflict Risk

"AI-generated or AI-assisted data analysis outputs" carves out a clear, narrow niche (GenAI disclosure for data analysis) with terms unlikely to be confused with other skills, matching the level-3 anchor of a clear distinct niche.

3 / 3

Total

9

/

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
dathere/qsv
Reviewed

Table of Contents

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