ideogram-data-handling
Implement Ideogram PII handling, data retention, and GDPR/CCPA compliance patterns. Use when handling sensitive data, implementing data redaction, configuring retention policies, or ensuring compliance with privacy regulations for Ideogram integrations. Trigger with phrases like "ideogram data", "ideogram PII", "ideogram GDPR", "ideogram data retention", "ideogram privacy", "ideogram CCPA".
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill ideogram-data-handling80
Does it follow best practices?
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npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-structured skill description with explicit trigger guidance and clear 'Use when' clauses. The Ideogram-specific focus provides strong distinctiveness. The main weakness is that the capability descriptions could be more concrete with specific actions rather than general patterns like 'compliance patterns'.
Suggestions
Add more specific concrete actions beyond patterns, such as 'mask user identifiers', 'configure auto-deletion schedules', or 'generate compliance audit reports' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Ideogram PII/privacy compliance) and lists some actions like 'data redaction', 'configuring retention policies', but the actions are somewhat general patterns rather than multiple concrete specific operations. | 2 / 3 |
Completeness | Clearly answers both what (implement PII handling, data retention, GDPR/CCPA compliance patterns) and when (explicit 'Use when...' clause plus 'Trigger with phrases like...' section providing clear guidance). | 3 / 3 |
Trigger Term Quality | Explicitly lists natural trigger phrases users would say: 'ideogram data', 'ideogram PII', 'ideogram GDPR', 'ideogram data retention', 'ideogram privacy', 'ideogram CCPA'. Good coverage of relevant terms with the Ideogram prefix. | 3 / 3 |
Distinctiveness Conflict Risk | The 'Ideogram' prefix on all trigger terms creates a clear niche. This skill is specifically for Ideogram integrations' privacy compliance, making it unlikely to conflict with generic privacy or other platform-specific skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides solid, actionable code examples for Ideogram data handling with good coverage of PII detection, redaction, and GDPR/CCPA compliance. However, it lacks validation checkpoints for critical operations like data deletion, and could be more concise by removing prerequisite explanations and better organizing content across files.
Suggestions
Add explicit validation steps after deletion operations (e.g., verify deletion completed, check for orphaned data) to improve workflow clarity for these destructive operations
Remove the Prerequisites section - Claude already understands GDPR/CCPA concepts and SDK requirements
Consider moving detailed code implementations (full DSAR export, retention cleanup) to separate reference files, keeping SKILL.md as a concise overview with quick examples
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is reasonably efficient but includes some unnecessary elements like the Prerequisites section explaining concepts Claude knows, and the data classification table could be more compact. The code examples are appropriately sized but some explanatory text is redundant. | 2 / 3 |
Actionability | Provides fully executable TypeScript code for PII detection, redaction, data cleanup, DSAR exports, and deletion. All code examples are copy-paste ready with concrete implementations including regex patterns, database operations, and cron scheduling. | 3 / 3 |
Workflow Clarity | Steps are listed in the Instructions section but lack validation checkpoints. For data deletion and GDPR operations (which are destructive/compliance-critical), there are no explicit verification steps or feedback loops to confirm successful completion before proceeding. | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but the file is somewhat monolithic with all code inline. The external references at the end are appropriate, but detailed implementations like the full DSAR export or retention cleanup could be split into separate reference files. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Reviewed
Table of Contents
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