feat: add Claude Code skill for Data Designer library #309
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Greptile OverviewGreptile Summary
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| Filename | Overview |
|---|---|
| packages/data-designer-config/src/data_designer/config/init.py | Exports ConstraintType and InequalityOperator via TYPE_CHECKING and lazy imports; small API-surface fix. |
| skill/README.md | Adds setup instructions for installing and using the Claude Code skill; includes download commands for the skill folder. |
| skill/data-designer/SKILL.md | Introduces core skill definition and workflow docs; currently instructs capturing 'chain-of-thought' via extract_reasoning_content. |
| skill/data-designer/hooks/check_data_designer.sh | Adds session-start hook to detect data_designer installation and print version/path context. |
| skill/data-designer/references/advanced_patterns.md | Adds advanced usage guide; currently recommends storing chain-of-thought via extract_reasoning_content. |
| skill/data-designer/references/api_reference.md | Adds large API reference; includes wording that extract_reasoning_content captures 'chain-of-thought'. |
| skill/data-designer/scripts/helpers/pydantic_info_utils.py | Adds shared helper utilities for printing Pydantic model schemas/types, including nested model and enum expansion. |
| skill/test_info_scripts.py | Adds comprehensive unit/integration tests for the introspection scripts using subprocess uv runs. |
Sequence Diagram
sequenceDiagram
participant User
participant ClaudeCode as Claude Code
participant HookStart as check_data_designer.sh
participant InfoScripts as get_*_info.py
participant DD as data_designer (DataDesigner)
participant MCP as MCP Provider/Tools
participant HooksPost as ruff_lint.sh & ty_check.sh
User->>ClaudeCode: Activate data-designer skill
ClaudeCode->>HookStart: SessionStart hook (startup)
HookStart-->>ClaudeCode: Prints install/version/library path
User->>ClaudeCode: Describe dataset + requirements
ClaudeCode->>InfoScripts: (Optional) uv run get_column/sampler/processor/validator info
InfoScripts-->>ClaudeCode: Prints schema/field references
ClaudeCode->>DD: Build DataDesignerConfigBuilder + add columns
alt Tool-augmented generation
ClaudeCode->>DD: Configure ToolConfig(tool_alias, providers, allow_tools)
DD->>MCP: Call tool(s) via MCP during LLM column execution
MCP-->>DD: Tool results
end
ClaudeCode->>DD: validate(config_builder)
ClaudeCode->>DD: preview(config_builder, num_records=...)
ClaudeCode->>DD: create(config_builder, num_records=..., dataset_name=...)
ClaudeCode->>HooksPost: PostToolUse hook on Write/Edit
HooksPost-->>ClaudeCode: Lint/type-check edited file
![greptile-apps[bot]](https://avatars.githubusercontent.com/in/867647?s=60&v=4){kind=small}
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| ``` | ||
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| ### Trace & Reasoning Capture | ||
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| ```python | ||
| dd.LLMTextColumnConfig( | ||
| name="answer", | ||
| prompt="...", | ||
| model_alias="nvidia-reasoning", | ||
| with_trace=dd.TraceType.ALL_MESSAGES, # -> answer__trace column | ||
| extract_reasoning_content=True, # -> answer__reasoning_content column | ||
| ) | ||
| ``` |
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Encourages chain-of-thought capture
This skill docs recommend extract_reasoning_content=True and describe it as “capture chain-of-thought”. Persisting model reasoning content is typically disallowed/undesired (privacy/safety + provider ToS) and can also break runs if the underlying provider/model doesn’t return a separate reasoning field. Consider removing this recommendation (or reframing to capture tool traces only) and documenting safe alternatives (e.g., with_trace=TraceType.ALL_MESSAGES without extracting reasoning).
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: skill/data-designer/SKILL.md
Line: 247:259
Comment:
**Encourages chain-of-thought capture**
This skill docs recommend `extract_reasoning_content=True` and describe it as “capture chain-of-thought”. Persisting model reasoning content is typically disallowed/undesired (privacy/safety + provider ToS) and can also break runs if the underlying provider/model doesn’t return a separate reasoning field. Consider removing this recommendation (or reframing to capture tool traces only) and documenting safe alternatives (e.g., `with_trace=TraceType.ALL_MESSAGES` without extracting reasoning).
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
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| ## 8. Trace & Reasoning Extraction | ||
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| ### Trace Types | ||
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| - `TraceType.NONE` (default): No trace | ||
| - `TraceType.LAST_MESSAGE`: Only final response -> `{name}__trace` | ||
| - `TraceType.ALL_MESSAGES`: Full conversation -> `{name}__trace` | ||
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| ### Reasoning Content | ||
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| `extract_reasoning_content=True` creates `{name}__reasoning_content` with chain-of-thought. | ||
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| Available on all LLM column types. | ||
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| ### Use Cases | ||
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| - **Debugging**: `ALL_MESSAGES` to see full conversation including tool calls | ||
| - **Fine-tuning data**: `extract_reasoning_content=True` for clean reasoning extraction | ||
| - **Tool-use training**: `ALL_MESSAGES` to capture tool call patterns |
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Avoid persisting model reasoning
This section documents extract_reasoning_content=True as producing “chain-of-thought” and suggests using it for fine-tuning. Persisting model reasoning content is generally not appropriate (privacy/safety + provider policies), and it may not be supported consistently across providers/models. Recommend removing/rewriting this guidance to focus on safer debugging artifacts (e.g., tool traces / final outputs) rather than storing reasoning content.
Prompt To Fix With AI
This is a comment left during a code review.
Path: skill/data-designer/references/advanced_patterns.md
Line: 372:390
Comment:
**Avoid persisting model reasoning**
This section documents `extract_reasoning_content=True` as producing “chain-of-thought” and suggests using it for fine-tuning. Persisting model reasoning content is generally not appropriate (privacy/safety + provider policies), and it may not be supported consistently across providers/models. Recommend removing/rewriting this guidance to focus on safer debugging artifacts (e.g., tool traces / final outputs) rather than storing reasoning content.
How can I resolve this? If you propose a fix, please make it concise.
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| ```python | ||
| dd.LLMTextColumnConfig( | ||
| name: str, | ||
| prompt: str, # Jinja2 template | ||
| model_alias: str, | ||
| system_prompt: str | None = None, | ||
| tool_alias: str | None = None, # MCP tool reference | ||
| with_trace: dd.TraceType = TraceType.NONE, # NONE, LAST_MESSAGE, ALL_MESSAGES | ||
| extract_reasoning_content: bool = False, # -> {name}__reasoning_content | ||
| multi_modal_context: list[dd.ImageContext] | None = None, | ||
| drop: bool = False, |
There was a problem hiding this comment.
Reasoning field documentation
The API reference describes extract_reasoning_content as “capture chain-of-thought”. If the library intentionally supports extracting a separate reasoning field, this should be documented more carefully (what exactly is captured, which providers support it, and whether it’s safe/allowed to store). Otherwise, consider removing or rewording to avoid encouraging collection of chain-of-thought.
Prompt To Fix With AI
This is a comment left during a code review.
Path: skill/data-designer/references/api_reference.md
Line: 103:113
Comment:
**Reasoning field documentation**
The API reference describes `extract_reasoning_content` as “capture chain-of-thought”. If the library intentionally supports extracting a separate reasoning field, this should be documented more carefully (what exactly is captured, which providers support it, and whether it’s safe/allowed to store). Otherwise, consider removing or rewording to avoid encouraging collection of chain-of-thought.
How can I resolve this? If you propose a fix, please make it concise.
johnnygreco
commented
Feb 6, 2026
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| ConstraintType, | ||
| InequalityOperator, |
Contributor
Author
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ugh, these leaked over from a different PR 🤦♂️
nabinchha
reviewed
Feb 10, 2026
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nabinchha
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nabinchha
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How will we keep all code/docs in skills up to date?
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📋 Summary
Adds a comprehensive Claude Code skill that teaches Claude how to generate synthetic datasets using NVIDIA NeMo Data Designer. When activated, Claude can design and build complete data generation pipelines — choosing the right column types, writing prompts, wiring up dependencies, and iterating on previews — all from a natural language description of the dataset.
🔄 Changes
✨ Added
skill/data-designer/SKILL.md— Core skill definition with step-by-step workflow, column type decision tree, key patterns (Jinja2 templating, seed datasets, constraints, processors, validators), and best practicesskill/data-designer/examples/— 5 runnable pattern-reference scripts:basic_text_generation.py— Sampler + expression + LLM text columnsstructured_and_code.py— Pydantic structured output + -seed_dataset_with_judge.py— Seed data + LLM judge scoringcustom_column_with_llm.py—@custom_column_generatorwith multi-model orchestrationmcp_tool_use.py— MCP tool calling with trace captureskill/data-designer/references/— Complete API reference (api_reference.md) and advanced patterns guide (advanced_patterns.md)skill/data-designer/scripts/— Discovery tools for API introspection (get_column_info.py,get_sampler_info.py,get_processor_info.py,get_validator_info.py, and sharedpydantic_info_utils.py)skill/data-designer/hooks/— Session hooks for environment checks (check_data_designer.sh), ruff linting (ruff_lint.sh), and ty type checking (ty_check.sh)skill/README.md— Setup instructions and quick start guideskill/test_info_scripts.py— 900-line test suite for the discovery scripts🔧 Changed
AGENTS.md— AddedEmbeddingColumnConfigandCustomColumnConfigto the column configuratiopackages/data-designer-config/src/data_designer/config/__init__.py** — Added missingConstraintTypeandInequalityOperatorexports to lazy imports🔍 Attention Areas
skill/data-designer/SKILL.md— Core skill definition that drives Claude's behavior; verify the workflow, decision tree, and patterns are accurate and completeskill/data-designer/references/api_reference.md— Complete API documentation (557 lines); ensure accuracy against current codebasepackages/data-designer-config/src/data_designer/config/__init__.py— Nets (ConstraintType,InequalityOperator) that affect the user-facing API surface🤖 Generated with AI