fireflies-data-handling
Handle Fireflies.ai transcript data: export formats, PII redaction, retention policies, and compliance. Use when exporting transcripts, implementing data redaction, configuring retention, or ensuring GDPR/CCPA compliance. Trigger with phrases like "fireflies data", "fireflies PII", "fireflies GDPR", "fireflies data retention", "fireflies privacy", "fireflies export".
84
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
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 well-crafted skill description that excels across all dimensions. It clearly identifies the product domain (Fireflies.ai), lists specific capabilities (export, PII redaction, retention, compliance), provides explicit 'Use when' guidance, and includes natural trigger phrases. The description is concise yet comprehensive, making it easy for Claude to select this skill appropriately.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: export formats, PII redaction, retention policies, and compliance. Further elaborates with exporting transcripts, implementing data redaction, configuring retention, and ensuring GDPR/CCPA compliance. | 3 / 3 |
Completeness | Clearly answers both 'what' (handle transcript data: export formats, PII redaction, retention policies, compliance) and 'when' (explicit 'Use when...' clause plus 'Trigger with phrases like...' providing concrete trigger guidance). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms including 'fireflies data', 'fireflies PII', 'fireflies GDPR', 'fireflies data retention', 'fireflies privacy', 'fireflies export'. These are terms users would naturally use when seeking help with Fireflies.ai data handling. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific product name 'Fireflies.ai' combined with domain-specific actions like PII redaction and GDPR/CCPA compliance for transcript data. Very unlikely to conflict with other skills. | 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 highly actionable skill with complete, executable TypeScript code covering multiple Fireflies.ai data handling scenarios. Its main weaknesses are the lack of validation checkpoints for destructive operations (retention cleanup, GDPR deletion) and the monolithic structure that packs ~200 lines of code into a single file without supporting bundle files. The content could be more concise by trimming redundant sections like 'Output' and 'Prerequisites'.
Suggestions
Add a dry-run mode and explicit confirmation/validation step before the retention policy deletes transcripts — e.g., log what would be deleted, require confirmation, then proceed.
Split the export formats, PII patterns, and retention logic into separate bundle files (e.g., `export-formats.ts`, `pii-redaction.ts`, `retention-policy.ts`) and reference them from the main SKILL.md overview.
Complete the GDPR handler with concrete redaction-per-person code instead of leaving 'Option 1 / Option 2' as comments — this is a critical compliance workflow that needs explicit guidance.
Remove the 'Output' section (it restates the steps) and trim 'Prerequisites' to just the API key requirement.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly efficient with executable code examples, but includes some unnecessary sections like 'Prerequisites' with obvious items ('Understanding of transcript data structure'), an 'Output' section that just restates what the steps already cover, and inline comments that explain obvious things. The code itself is well-structured but could be tighter. | 2 / 3 |
Actionability | Fully executable TypeScript code with complete implementations for each step: GraphQL queries, export formatters, PII regex patterns, retention logic, and GDPR handling. Code is copy-paste ready with proper error handling, rate limiting, and helper functions included. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced and numbered, but there are no explicit validation checkpoints between steps. For destructive operations like retention cleanup (deleting transcripts), there's no dry-run mode, confirmation step, or validation before proceeding with deletions. The GDPR handler identifies affected transcripts but leaves the actual action as comments ('Option 1' / 'Option 2') without concrete guidance. | 2 / 3 |
Progressive Disclosure | The content is a long monolithic file (~200+ lines of code) that could benefit from splitting export formats, PII patterns, and retention logic into separate referenced files. The 'Next Steps' reference to 'fireflies-enterprise-rbac' is good, but no bundle files exist to support progressive disclosure. The error handling table is a nice compact reference though. | 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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- Reviewed
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