langfuse-data-handling
Manage Langfuse data export, retention, and compliance requirements. Use when exporting trace data, configuring retention policies, or implementing data compliance for LLM observability. Trigger with phrases like "langfuse data export", "langfuse retention", "langfuse GDPR", "langfuse compliance", "export langfuse traces".
64
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/langfuse-pack/skills/langfuse-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 well-structured skill description that excels in completeness and distinctiveness by providing explicit 'Use when' and 'Trigger with' clauses targeting a clear niche (Langfuse data management). The main weakness is that the capability descriptions could be more granular—listing specific concrete actions rather than broad categories like 'manage export, retention, and compliance'. Overall it is a strong description that would perform well in skill selection.
Suggestions
Increase specificity by listing more concrete actions, e.g., 'Export trace data to CSV/JSON, configure TTL retention policies, handle GDPR deletion requests, audit data access logs' instead of the broader 'manage export, retention, and compliance'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Langfuse data management) and some actions (export, retention, compliance), but the actions are somewhat high-level rather than listing multiple concrete specific operations like 'export trace data to CSV, configure TTL retention policies, delete user data for GDPR requests'. | 2 / 3 |
Completeness | Clearly answers both 'what' (manage Langfuse data export, retention, and compliance) and 'when' (explicit 'Use when' clause with specific triggers, plus a 'Trigger with phrases like' section providing concrete activation terms). | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms that users would actually say: 'langfuse data export', 'langfuse retention', 'langfuse GDPR', 'langfuse compliance', 'export langfuse traces'. These cover multiple natural variations and are specific to the skill's niche. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of Langfuse + data export/retention/compliance. The trigger terms are narrowly scoped to Langfuse data management, making it very unlikely to conflict with other 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 a comprehensive set of Langfuse data handling scenarios. Its main weaknesses are the lack of validation/verification steps for destructive operations (deletion, retention enforcement) and significant code duplication in pagination patterns. The content would benefit from being split into focused sub-files and adding safety guardrails for irreversible actions.
Suggestions
Add a dry-run mode and confirmation/verification step to handleDeletionRequest and enforceRetention — e.g., log what will be deleted, require explicit confirmation, then verify deletion count matches expected count.
Extract the repeated pagination pattern into a shared helper function to reduce duplication and improve conciseness.
Split GDPR handling and anonymization into separate referenced files (e.g., GDPR.md, ANONYMIZATION.md) to improve progressive disclosure and keep the main skill as a concise overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly long with repetitive pagination patterns across multiple functions. The pagination boilerplate is duplicated in exportTraces, exportScores, and enforceRetention. The prerequisites section explaining 'Understanding of your compliance requirements' is unnecessary padding. However, most content is functional code rather than explanation. | 2 / 3 |
Actionability | All guidance is provided as fully executable TypeScript code with concrete examples covering export, retention, GDPR access/erasure, and anonymization. Functions include rate limiting, pagination, and file output — ready to adapt and use directly. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced and labeled, but validation checkpoints are missing for destructive operations. The deletion function (handleDeletionRequest) has no confirmation step, dry-run mode, or verification that all traces were actually deleted. The enforceRetention function similarly lacks a validation/verification step after bulk deletion. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and helpful reference tables, but it's a monolithic document (~200 lines of code) with no bundle files to offload detail. The anonymization and GDPR sections could be separate files referenced from the overview. External resource links are provided but internal progressive disclosure is absent. | 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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