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gdpr-data-handling

Implement GDPR-compliant data handling with consent management, data subject rights, and privacy by design. Use when building systems that process EU personal data, implementing privacy controls, or conducting GDPR compliance reviews.

64

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./skills/gdpr-data-handling/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%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 skill body is concise and well-sectioned but provides only generic, non-actionable instructions instead of concrete GDPR-specific guidance, and its sole reference points to a nonexistent file. Strong on token efficiency, weak on substance.

Suggestions

Replace the abstract instructions with concrete, GDPR-specific steps, e.g. capturing lawful basis, recording consent with timestamp and scope, and fulfilling DSR types (access, erasure, portability) with example data structures or commands.

Add an explicit validation checkpoint/feedback loop, such as verifying consent records exist before processing or confirming a DSR response is complete and within the statutory deadline.

Fix the broken reference: create resources/implementation-playbook.md (or move it to the conventional references/ directory) so the signaled detailed patterns actually resolve.

DimensionReasoningScore

Conciseness

The body is lean with no concept explanations Claude already knows and no padding; every section is short and token-efficient.

3 / 3

Actionability

The instructions are abstract boilerplate ('Clarify goals...', 'Apply relevant best practices...', 'Provide actionable steps and verification.') with no concrete code, commands, or specific GDPR patterns, matching the vague/describes-rather-than-instructs anchor.

1 / 3

Workflow Clarity

A loose sequence exists (clarify, apply, validate) but checkpoints are only implicit and 'validate outcomes' is a vague directive rather than an explicit validation step with feedback loops.

2 / 3

Progressive Disclosure

One reference is signaled one level deep ('resources/implementation-playbook.md'), but the referenced file and directory do not exist, so navigation is broken and the path deviates from the standard references/ layout.

2 / 3

Total

8

/

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 well-crafted: it states concrete capabilities, includes natural trigger terms, answers both what and when, and occupies a clear niche. It uses third-person voice with no padding.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities ('consent management, data subject rights, and privacy by design') rather than vague language, matching the multiple-specific-actions anchor.

3 / 3

Completeness

Explicitly answers what it does ('Implement GDPR-compliant data handling...') and when to use it ('Use when building systems that process EU personal data...').

3 / 3

Trigger Term Quality

Natural trigger terms a user would say ('GDPR', 'EU personal data', 'privacy controls', 'compliance reviews') provide good coverage rather than technical jargon.

3 / 3

Distinctiveness Conflict Risk

The GDPR/EU-personal-data niche has distinct triggers and is 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
rmyndharis/antigravity-skills
Reviewed

Table of Contents

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