apollo-data-handling
Apollo.io data management and compliance. Use when handling contact data, implementing GDPR compliance, or managing data exports and retention. Trigger with phrases like "apollo data", "apollo gdpr", "apollo compliance", "apollo data export", "apollo data retention", "apollo pii".
80
77%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/apollo-pack/skills/apollo-data-handling/SKILL.mdQuality
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 solid skill description that clearly identifies its niche (Apollo.io data management and compliance) and provides explicit trigger guidance. Its main weakness is that the capability descriptions are somewhat high-level—listing more concrete actions would strengthen it. The explicit trigger phrases and 'Use when' clause make it effective for skill selection.
Suggestions
Add more specific concrete actions, e.g., 'Delete or anonymize contact records, generate GDPR compliance reports, configure data retention policies, export contact lists' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Apollo.io data management) and mentions some actions like 'handling contact data', 'implementing GDPR compliance', 'managing data exports and retention', but these are fairly high-level rather than listing multiple concrete specific actions (e.g., no mention of specific operations like deleting records, anonymizing fields, generating compliance reports). | 2 / 3 |
Completeness | Clearly answers both 'what' (Apollo.io data management and compliance, handling contact data, GDPR compliance, data exports and retention) and 'when' (explicit 'Use when...' clause and 'Trigger with phrases like...' providing clear activation guidance). | 3 / 3 |
Trigger Term Quality | Includes a good set of natural trigger terms that users would actually say: 'apollo data', 'apollo gdpr', 'apollo compliance', 'apollo data export', 'apollo data retention', 'apollo pii'. These cover multiple relevant variations and are specific to the tool. | 3 / 3 |
Distinctiveness Conflict Risk | The description is clearly scoped to Apollo.io specifically, with distinct triggers that include the 'apollo' prefix. This makes it very unlikely to conflict with generic data management or GDPR 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 highly actionable, executable TypeScript code covering GDPR compliance operations with real Apollo API endpoints, which is its primary strength. However, it's verbose for a skill file — the inline code for encryption and audit logging could be referenced rather than fully included. The most significant weakness is the lack of validation checkpoints for destructive operations like batch retention cleanup, which should include dry-run modes or confirmation steps.
Suggestions
Add a dry-run/preview mode to the retention enforcement function before performing batch deletes, and include an explicit validation step confirming deletion success
Move detailed implementations (encryption, audit logging) to separate referenced files and keep SKILL.md as a concise overview with quick-start examples
Remove the overview explanation of what Apollo's database contains and what PII stands for — Claude already knows these concepts
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill provides substantial executable code which is valuable, but is quite lengthy (~200 lines). The overview paragraph explaining what Apollo's database contains (275M+ contacts) and what PII means is unnecessary context for Claude. The encryption and audit logging sections, while useful, add significant length for what could be more concisely presented. | 2 / 3 |
Actionability | Fully executable TypeScript code with real Apollo API endpoints, proper type definitions, and concrete implementations for each operation. The code is copy-paste ready with actual API paths like '/contacts/search' and '/people/match', and includes practical details like needing master API key for deletes. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced and the erasure workflow correctly orders operations (remove from sequences before deleting). However, there are no explicit validation checkpoints — the retention policy performs batch deletions without a dry-run or confirmation step, and the erasure handler doesn't verify the contact was actually deleted. Missing feedback loops for these destructive batch operations caps this at 2. | 2 / 3 |
Progressive Disclosure | The content is structured with clear sections and a helpful error handling table, but all code is inline in a single long file rather than being split into referenced files. The 'Next Steps' reference to apollo-enterprise-rbac is good, but the bulk of the content could benefit from being organized as a quick-start overview with references to detailed implementation 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 | |
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