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dlt-connector

Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.

74

Quality

92%

Does it follow best practices?

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SecuritybySnyk

High

Do not use without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

A well-structured, actionable skill body that walks a four-phase workflow with strong validation feedback loops and clean progressive disclosure to real bundle files. Slightly verbose in places and some code templates rely on placeholders, but overwhelmingly executable and clear.

Suggestions

Tighten the 'Who this is for' and 'Important notes' sections, which partially restate guidance already embedded in the phase steps, to reduce token cost.

Replace the `<source_function>` placeholder in the pipeline template with one concrete worked example (e.g., a HubSpot call from dlt_sources) so the pattern is fully copy-pasteable before users consult the reference.

Consolidate the catalog-naming guidance so it lives in one place rather than being repeated across 'Critical', Phase 2, and Troubleshooting sections.

DimensionReasoningScore

Conciseness

Largely lean and command-driven with concrete snippets throughout, but includes some explanatory prose (e.g., the 'Who this is for' framing and 'Important notes' restating earlier points) that could be trimmed; not a 5 because minor instances of over-explanation remain.

4 / 5

Actionability

Provides copy-paste-ready bash and Python for install, pipeline, introspection, profile setup, and wren build/query, but some templates use placeholders like `<source_function>` and `<table_name>` that the user must fill in, leaving minor gaps.

4 / 5

Workflow Clarity

A clearly sequenced four-phase workflow (Extract→Model→Build & Verify→Handoff) with explicit validation checkpoints and a validate→debug→fix→retry feedback loop, capped by 'Only after queries return real data, tell the user the setup is complete.'

5 / 5

Progressive Disclosure

SKILL.md is an overview with well-signaled, one-level-deep references to the bundled `dlt_sources` reference and `introspect_dlt` script (both confirmed present), with fetch commands provided; detailed source templates and introspection logic are appropriately split out.

5 / 5

Total

18

/

20

Passed

Description

100%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.

A strong, third-person description that clearly states what the skill does and gives comprehensive, natural trigger conditions including named SaaS sources and a secondary entry point for existing DuckDB files. No verbosity or over-claims; distinct and conflict-resistant.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both what (the full extract→model→build→handoff flow) and when ('Use this skill whenever the user mentions...' plus the dlt-produced DuckDB file trigger) with concrete trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural trigger phrases users would actually say: 'connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, setting up a new data source from a REST API', including named products and synonyms.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (dlt + Wren Engine + SaaS-to-SQL) with distinct triggers naming specific SaaS products and the Wren/dlt toolchain, minimizing overlap with generic data or PDF skills.

5 / 5

Total

20

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
Canner/WrenAI
Reviewed

Table of Contents

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