gamma-data-handling

Handle data privacy, retention, and compliance for Gamma integrations. Use when implementing GDPR compliance, data retention policies, or managing user data within Gamma workflows. Trigger with phrases like "gamma data", "gamma privacy", "gamma GDPR", "gamma data retention", "gamma compliance".

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

65%

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

The content is highly actionable with complete, executable TypeScript for every step, but it over-inlines material that already lives in references/implementation.md and omits validation/feedback checkpoints for its destructive batch operations. Tightening the duplication and adding verify steps would lift the conciseness and workflow-clarity scores.

Suggestions

Add explicit validation checkpoints to the destructive/batch workflows, e.g. after enforceRetention or GDPR erasure, confirm affected-row counts before/after and log a verification result so errors are caught early.

Replace the duplicated inline Step 4 (retention) and Step 5 (GDPR) with a clear pointer to references/implementation.md, keeping only a concise summary in the body to avoid the same content appearing in two places.

Trim the ASCII data-flow map and the data-classification table where their information is already conveyed by the code comments, to recover token budget.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient and code-driven, but the inline five-step implementation duplicates much of what is also in references/implementation.md (consent, retention, GDPR), and the ASCII data-flow map plus classification table add length that partially restates what Claude can infer from the code.	2 / 3
Actionability	Each step ships fully executable TypeScript (sanitize.ts, logging.ts, exports.ts, retention.ts, GDPR handler) with real imports, env vars, and SDK calls rather than pseudocode, making the guidance copy-paste ready.	3 / 3
Workflow Clarity	The five steps are sequenced, but destructive/batch operations (S3 deletion, log anonymization, GDPR erasure) lack validation checkpoints or feedback loops; enforceRetention mutates a single cutoff date across steps with no verify step, and the rubric caps such operations at 2 without validation.	2 / 3
Progressive Disclosure	There is a real one-level reference (references/implementation.md) and section headings, but the body never signals that file — the inline Steps 4-5 duplicate the reference's retention/GDPR content instead of pointing to it, so content that should be separated is inline and the reference is not clearly navigated to.	2 / 3
	Total	9 / 12 Passed

Description

90%

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 strong on triggers, completeness, and distinctiveness thanks to explicit Gamma-scoped trigger phrases and a clear Use-when clause. Its only weakness is specificity, where capabilities are stated as abstract categories rather than concrete, enumerated actions.

Suggestions

Replace abstract capability categories with concrete verbs, e.g. "Sanitize PII before Gamma API calls, enforce retention policies, and handle GDPR access/erasure requests" so the description lists multiple specific actions.

Lead with the concrete actions and keep the trigger-phrase list, but tighten the multi-line structure into a more compact single description to avoid unnecessary padding.

Dimension	Reasoning	Score
Specificity	The description names the domain ("data privacy, retention, and compliance for Gamma integrations") but lists the capabilities as abstract categories rather than multiple concrete actions like "sanitize PII," "enforce retention policies," or "handle GDPR erasure requests."	2 / 3
Completeness	It clearly answers what the skill does and includes an explicit "Use when implementing GDPR compliance, data retention policies, or managing user data" clause plus enumerated trigger phrases, satisfying both the what and the when.	3 / 3
Trigger Term Quality	It provides explicit natural trigger phrases a user would actually say ("gamma data", "gamma privacy", "gamma GDPR", "gamma data retention", "gamma compliance"), giving good coverage of common variations.	3 / 3
Distinctiveness Conflict Risk	The Gamma-specific trigger namespace ("gamma data", "gamma privacy", etc.) carves out a clear niche that is unlikely to collide with other skills' triggers.	3 / 3
	Total	11 / 12 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/claude-code-plugins-plus-skills
Commit: 1628598

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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