groq-data-handling
Implement prompt sanitization, PII redaction, response filtering, and usage tracking for Groq API integrations. Trigger with phrases like "groq data", "groq PII", "groq GDPR", "groq data retention", "groq privacy", "groq compliance".
84
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%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 strong skill description that clearly specifies concrete capabilities (sanitization, redaction, filtering, tracking), targets a specific platform (Groq API), and provides explicit trigger phrases. The description uses proper third-person voice and covers both what the skill does and when to use it effectively.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'prompt sanitization', 'PII redaction', 'response filtering', and 'usage tracking' for a specific platform (Groq API integrations). | 3 / 3 |
Completeness | Clearly answers both 'what' (prompt sanitization, PII redaction, response filtering, usage tracking for Groq API) and 'when' (explicit trigger phrases provided with 'Trigger with phrases like...'). | 3 / 3 |
Trigger Term Quality | Provides good coverage of natural trigger terms users would say: 'groq data', 'groq PII', 'groq GDPR', 'groq data retention', 'groq privacy', 'groq compliance'. These are realistic phrases a user concerned about data handling with Groq would use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of Groq API + data privacy/compliance concerns. The trigger terms are all prefixed with 'groq' making conflicts with generic privacy or other API skills unlikely. | 3 / 3 |
Total | 12 / 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 is a solid, actionable skill with fully executable TypeScript code covering PII redaction, usage tracking, audit logging, and content moderation for Groq API integrations. Its main weaknesses are the lack of validation/verification steps for the sensitive PII redaction workflow and the monolithic structure that could benefit from splitting detailed implementations into referenced files. The time-sensitive pricing data will also become stale.
Suggestions
Add explicit validation steps for PII redaction, such as a test function that verifies regex patterns against sample inputs and confirms no PII leaks before proceeding.
Split the detailed implementation code (cost tracking, audit logging, content moderation) into separate referenced files, keeping SKILL.md as a concise overview with the core sanitization pattern.
Move the COST_PER_1M pricing table to a separate config file or add a note that prices should be verified against current Groq pricing, since these values will become stale.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with executable code, but includes some unnecessary elements like the Groq data policy section (which Claude can look up) and the cost-per-million pricing table which is time-sensitive and will become stale. The code blocks are substantial but largely earn their place as they form a complete implementation. | 2 / 3 |
Actionability | Fully executable TypeScript code throughout with concrete regex patterns, typed interfaces, specific model names, pricing data, and copy-paste ready functions. Each step produces a usable component that builds on the previous one. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced and build on each other (sanitize → wrap → track → audit → moderate → report), but there are no explicit validation checkpoints or feedback loops. For a skill involving PII redaction (a destructive/sensitive operation), there should be verification steps like testing the regex patterns against sample data or validating that redaction was complete before sending. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and a helpful error handling table, but the skill is quite long (~200 lines of code) and could benefit from splitting detailed implementations (e.g., cost tracking, audit logging) into separate reference files. The single reference to 'groq-enterprise-rbac' is good but insufficient for the volume of inline content. | 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 | |
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