groq-data-handling

Use when you need to keep PII out of Groq API calls, filter model responses, audit-log conversations, or track token cost and usage for a Groq integration. Implements prompt sanitization, PII redaction, response filtering, and usage tracking. Trigger with phrases like "groq data", "groq PII", "groq GDPR", "groq data retention", "groq privacy", "groq compliance".

Quality

85%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Quality

Content

78%Weight 40%Scale 1-5

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

The body is well-structured and efficient, using progressive disclosure to keep the overview lean while pointing to complete executable code in real reference files. The main improvement area is workflow clarity, where an explicit validation/retry loop would strengthen the pipeline guidance.

Suggestions

Add an explicit validation step in the pipeline (e.g., verify hadPII/responseFiltered flags and decide whether to retry or halt) to create a validate->fix->retry feedback loop.

Trim the repeated reference links (Resources section largely duplicates links already inline in Examples) to recover a few tokens.

Either make the inline code snippets fully executable or explicitly label them as illustrative skeletons to avoid ambiguity about their runnability.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence, adding genuinely non-obvious facts (e.g., Groq's training-data policy) rather than padding; minor extra tokens come from the error-handling table and repeated resource links, which could be trimmed slightly.	4 / 5
Actionability	Inline skeletons are explicitly justified as pointers to full copy-ready code in references/implementation.md, and a minimal end-to-end snippet ('const { content, audit } = await auditedCompletion(...)') is provided; minor gaps remain in the inline skeletons themselves.	4 / 5
Workflow Clarity	The four-stage pipeline (sanitize -> wrap -> track -> audit) is clearly sequenced and paired with a diagnostic error-handling table, but there is no explicit validate->fix->retry feedback loop in the main flow.	4 / 5
Progressive Disclosure	SKILL.md is a concise overview that signals one-level-deep references (references/implementation.md, references/examples.md), both of which exist as real bundle files and are clearly linked from multiple sections.	5 / 5
	Total	17 / 20 Passed

Description

92%Weight 40%Scale 1-5

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, complete, and well-targeted, explicitly stating both what the skill does and when to use it with concrete Groq-scoped trigger phrases. Its only mild weakness is trigger-term naturalness, where the phrases lean compliance-heavy and could add a few everyday synonyms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('keep PII out of Groq API calls, filter model responses, audit-log conversations, or track token cost and usage' plus 'prompt sanitization, PII redaction, response filtering, and usage tracking'), giving comprehensive coverage rather than vague language.	5 / 5
Completeness	Explicitly answers both 'what' ('Implements prompt sanitization, PII redaction, response filtering, and usage tracking') and 'when' ('Use when you need to keep PII out of Groq API calls...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Provides natural trigger phrases ('groq data', 'groq PII', 'groq GDPR', 'groq privacy', 'groq compliance') with good coverage, but the terms lean toward compliance jargon and omit a few everyday synonyms like 'groq cost' or 'groq audit' that a user might naturally say.	4 / 5
Distinctiveness Conflict Risk	Scoped tightly to Groq API data handling with groq-prefixed triggers, occupying a clear niche with minimal overlap risk against other skills.	5 / 5
	Total	19 / 20 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 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	14 / 16 Passed

Repository: jeremylongshore/tons-of-skills-marketplace
Path: plugins/saas-packs/groq-pack/skills/groq-data-handling/SKILL.md
Commit: 88dcf65

Reviewed: 3 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.