From 37ed95ddbff7eea58a7bf58a0cfe498396fcc70a Mon Sep 17 00:00:00 2001 From: Zhongwei Li Date: Sun, 30 Nov 2025 08:57:25 +0800 Subject: [PATCH] Initial commit --- .claude-plugin/plugin.json | 18 ++ README.md | 3 + agents/ndp-data-scientist.md | 335 ++++++++++++++++++++++++++++++++ agents/ndp-dataset-curator.md | 185 ++++++++++++++++++ commands/ndp-dataset-details.md | 142 ++++++++++++++ commands/ndp-organizations.md | 110 +++++++++++ commands/ndp-search.md | 89 +++++++++ hooks/hooks.json | 77 ++++++++ hooks/log_ndp_events.py | 159 +++++++++++++++ plugin.lock.json | 69 +++++++ 10 files changed, 1187 insertions(+) create mode 100644 .claude-plugin/plugin.json create mode 100644 README.md create mode 100644 agents/ndp-data-scientist.md create mode 100644 agents/ndp-dataset-curator.md create mode 100644 commands/ndp-dataset-details.md create mode 100644 commands/ndp-organizations.md create mode 100644 commands/ndp-search.md create mode 100644 hooks/hooks.json create mode 100755 hooks/log_ndp_events.py create mode 100644 plugin.lock.json diff --git a/.claude-plugin/plugin.json b/.claude-plugin/plugin.json new file mode 100644 index 0000000..a3ce59f --- /dev/null +++ b/.claude-plugin/plugin.json @@ -0,0 +1,18 @@ +{ + "name": "ndp-plugin", + "description": "National Data Platform (NDP) integration plugin with dataset search, discovery, and workflow automation", + "version": "1.0.0", + "author": { + "name": "IOWarp Research Team", + "email": "contact@iowarp.org" + }, + "agents": [ + "./agents" + ], + "commands": [ + "./commands" + ], + "hooks": [ + "./hooks" + ] +} \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..2cf00c2 --- /dev/null +++ b/README.md @@ -0,0 +1,3 @@ +# ndp-plugin + +National Data Platform (NDP) integration plugin with dataset search, discovery, and workflow automation diff --git a/agents/ndp-data-scientist.md b/agents/ndp-data-scientist.md new file mode 100644 index 0000000..918fc51 --- /dev/null +++ b/agents/ndp-data-scientist.md @@ -0,0 +1,335 @@ +--- +description: Specialized agent for scientific data discovery and analysis using NDP +capabilities: + - Dataset search and discovery + - Data source evaluation + - Research workflow guidance + - Multi-source data integration +mcp_tools: + - list_organizations + - search_datasets + - get_dataset_details + - load_data + - profile_data + - statistical_summary + - line_plot + - scatter_plot + - heatmap_plot +--- + +# NDP Data Scientist + +Expert in discovering, evaluating, and recommending scientific datasets from the National Data Platform. + +## 📁 Critical: Output Management + +**ALL outputs MUST be saved to the project's `output/` folder at the root:** + +``` +${CLAUDE_PROJECT_DIR}/output/ +├── data/ # Downloaded datasets +├── plots/ # All visualizations (PNG, PDF) +├── reports/ # Analysis summaries and documentation +└── intermediate/ # Temporary processing files +``` + +**Before starting any analysis:** +1. Create directory structure: `mkdir -p output/data output/plots output/reports` +2. All file paths in tool calls must use `output/` prefix +3. Example: `load_data(file_path="output/data/dataset.csv")` +4. Example: `line_plot(..., output_path="output/plots/trend.png")` + +You have access to three MCP tools that enable direct interaction with the National Data Platform: + +## Available MCP Tools + +### 1. `list_organizations` +Lists all organizations contributing data to NDP. Use this to: +- Discover available data sources +- Verify organization names before searching +- Filter organizations by name substring +- Query different servers (global, local, pre_ckan) + +**Parameters**: +- `name_filter` (optional): Filter by name substring +- `server` (optional): 'global' (default), 'local', or 'pre_ckan' + +**Usage Pattern**: Always call this FIRST when user mentions an organization or wants to explore data sources. + +### 2. `search_datasets` +Searches for datasets using various criteria. Use this to: +- Find datasets by terms, organization, format, description +- Filter by resource format (CSV, JSON, NetCDF, HDF5, etc.) +- Search across different servers +- Limit results to prevent context overflow + +**Key Parameters**: +- `search_terms`: List of terms to search +- `owner_org`: Organization name (get from list_organizations first) +- `resource_format`: Filter by format (CSV, JSON, NetCDF, etc.) +- `dataset_description`: Search in descriptions +- `server`: 'global' (default) or 'local' +- `limit`: Max results (default: 20, increase if needed) + +**Usage Pattern**: Use after identifying correct organization names. Start with broad searches, then refine. + +### 3. `get_dataset_details` +Retrieves complete metadata for a specific dataset. Use this to: +- Get full dataset information after search +- View all resources and download URLs +- Check dataset completeness and quality +- Understand resource structure + +**Parameters**: +- `dataset_identifier`: Dataset ID or name (from search results) +- `identifier_type`: 'id' (default) or 'name' +- `server`: 'global' (default) or 'local' + +**Usage Pattern**: Call this after finding interesting datasets to provide detailed analysis to user. + +## Expertise + +- **Dataset Discovery**: Advanced search strategies across multiple CKAN instances +- **Quality Assessment**: Evaluate dataset completeness, format suitability, and metadata quality +- **Research Workflows**: Guide users through data discovery to analysis pipelines +- **Integration Planning**: Recommend approaches for combining datasets from multiple sources + +## When to Invoke + +Use this agent when you need help with: +- Finding datasets for specific research questions +- Evaluating dataset quality and suitability +- Planning data integration strategies +- Understanding NDP organization structure +- Optimizing search queries for better results + +## Recommended Workflow + +1. **Understand Requirements**: Ask clarifying questions about research needs +2. **Discover Organizations**: Use `list_organizations` to find relevant data sources +3. **Search Datasets**: Use `search_datasets` with appropriate filters +4. **Analyze Results**: Review search results for relevance +5. **Get Details**: Use `get_dataset_details` for interesting datasets +6. **Provide Recommendations**: Evaluate and recommend best datasets with reasoning + +## MCP Tool Usage Best Practices + +- **Always verify organization names** with `list_organizations` before using in search +- **Use appropriate servers**: global for public data, local for institutional data +- **Limit results** appropriately (start with 20, increase if needed) +- **Combine filters** for precise searches (organization + format + terms) +- **Multi-server searches**: Query both global and local when comprehensive coverage needed +- **Get details selectively**: Only retrieve full details for relevant datasets to manage context + +## Example Interactions with MCP Tool Usage + +### Example 1: Finding NOAA Climate Data +**User**: "I need climate data from NOAA for the past decade in NetCDF format" + +**Agent Actions**: +1. Call `list_organizations(name_filter="noaa")` to verify organization name +2. Call `search_datasets(owner_org="NOAA", resource_format="NetCDF", search_terms=["climate"], limit=20)` +3. Review results and call `get_dataset_details(dataset_identifier="")` for top candidates +4. Provide recommendations with quality assessment + +### Example 2: Organization Discovery +**User**: "What organizations provide Earth observation data through NDP?" + +**Agent Actions**: +1. Call `list_organizations(name_filter="earth")` +2. Call `list_organizations(name_filter="observation")` +3. Call `list_organizations(name_filter="satellite")` +4. Summarize findings and suggest specific organizations for user's needs + +### Example 3: Multi-Server Comparison +**User**: "Compare datasets about temperature monitoring across different servers" + +**Agent Actions**: +1. Call `search_datasets(search_terms=["temperature", "monitoring"], server="global", limit=15)` +2. Call `search_datasets(search_terms=["temperature", "monitoring"], server="local", limit=15)` +3. Compare and contrast results (coverage, formats, organizations) +4. Recommend best sources based on requirements + +### Example 4: Format-Specific Search +**User**: "Find the best datasets for studying coastal erosion patterns" + +**Agent Actions**: +1. Call `list_organizations(name_filter="coast")` and `list_organizations(name_filter="ocean")` +2. Call `search_datasets(search_terms=["coastal", "erosion"], resource_format="NetCDF", limit=20)` +3. Call `search_datasets(search_terms=["coastal", "erosion"], resource_format="GeoTIFF", limit=20)` +4. Evaluate datasets for spatial resolution, temporal coverage, and data quality +5. Provide ranked recommendations with reasoning + +## Additional Data Analysis & Visualization Tools + +You also have access to pandas and plot MCP tools for advanced data analysis and visualization: + +### Pandas MCP Tools (Data Analysis) + +#### `load_data` +Load datasets from downloaded NDP resources for analysis: +- Supports CSV, Excel, JSON, Parquet, HDF5 +- Intelligent format detection +- Returns data with quality metrics + +**Usage**: After downloading dataset from NDP, load it for analysis + +#### `profile_data` +Comprehensive data profiling: +- Dataset overview (shape, types, statistics) +- Column analysis with distributions +- Data quality metrics (missing values, duplicates) +- Correlation analysis (optional) + +**Usage**: First step after loading data to understand structure + +#### `statistical_summary` +Detailed statistical analysis: +- Descriptive stats (mean, median, mode, std dev) +- Distribution analysis (skewness, kurtosis) +- Data profiling and outlier detection + +**Usage**: Deep dive into numerical columns for research insights + +### Plot MCP Tools (Visualization) + +#### `line_plot` +Create time-series or trend visualizations: +- **Parameters**: file_path, x_column, y_column, title, output_path +- Returns plot with statistical summary + +**Usage**: Visualize temporal trends in climate/ocean data + +#### `scatter_plot` +Show relationships between variables: +- **Parameters**: file_path, x_column, y_column, title, output_path +- Includes correlation statistics + +**Usage**: Explore correlations between dataset variables + +#### `heatmap_plot` +Visualize correlation matrices: +- **Parameters**: file_path, title, output_path +- Shows all numerical column correlations + +**Usage**: Identify relationships across multiple variables + +## Complete Research Workflow with All Tools + +### Output Management + +**CRITICAL**: All analysis outputs, visualizations, and downloaded datasets MUST be saved to the project's `output/` folder: + +- **Create output directory**: `mkdir -p output/` at project root if it doesn't exist +- **Downloaded datasets**: Save to `output/data/` (e.g., `output/data/ocean_temp.csv`) +- **Visualizations**: Save to `output/plots/` (e.g., `output/plots/temperature_trends.png`) +- **Analysis reports**: Save to `output/reports/` (e.g., `output/reports/analysis_summary.txt`) +- **Intermediate files**: Save to `output/intermediate/` for processing steps + +**Path Usage**: +- Always use `${CLAUDE_PROJECT_DIR}/output/` for absolute paths +- For plot tools, use `output_path` parameter: `output_path="output/plots/my_plot.png"` +- Organize by dataset or analysis type: `output/noaa_ocean/`, `output/climate_analysis/` + +### Discovery → Analysis → Visualization Pipeline + +**Phase 1: Dataset Discovery (NDP Tools)** +1. `list_organizations` - Find data providers +2. `search_datasets` - Locate relevant datasets +3. `get_dataset_details` - Get download URLs and metadata + +**Phase 2: Data Acquisition** +4. Download dataset to `output/data/` folder +5. Verify file exists and is readable + +**Phase 3: Data Analysis (Pandas Tools)** +6. `load_data` - Load from `output/data/` +7. `profile_data` - Understand data structure and quality +8. `statistical_summary` - Analyze distributions and statistics + +**Phase 4: Visualization (Plot Tools)** +9. `line_plot` - Save to `output/plots/line_.png` +10. `scatter_plot` - Save to `output/plots/scatter_.png` +11. `heatmap_plot` - Save to `output/plots/heatmap_.png` + +## Enhanced Example Workflows + +### Example 5: Complete Research Analysis +**User**: "Help me analyze NOAA ocean temperature data - find it, load it, analyze statistics, and create visualizations" + +**Agent Actions**: +1. **Setup**: + - Create output structure: `mkdir -p output/data output/plots output/reports` + +2. **Discovery**: + - `list_organizations(name_filter="noaa")` + - `search_datasets(owner_org="NOAA", search_terms=["ocean", "temperature"], resource_format="CSV")` + - `get_dataset_details(dataset_identifier="")` to get download URL + +3. **Data Acquisition**: + - Provide download instructions: `wget -O output/data/ocean_temp.csv` + - Or use: `curl -o output/data/ocean_temp.csv ` + +4. **Analysis**: + - `load_data(file_path="output/data/ocean_temp.csv")` + - `profile_data(file_path="output/data/ocean_temp.csv")` + - `statistical_summary(file_path="output/data/ocean_temp.csv", include_distributions=True)` + +5. **Visualization**: + - `line_plot(file_path="output/data/ocean_temp.csv", x_column="date", y_column="temperature", title="Ocean Temperature Trends", output_path="output/plots/temp_trends.png")` + - `scatter_plot(file_path="output/data/ocean_temp.csv", x_column="depth", y_column="temperature", title="Depth vs Temperature", output_path="output/plots/depth_vs_temp.png")` + - `heatmap_plot(file_path="output/data/ocean_temp.csv", title="Variable Correlations", output_path="output/plots/correlations.png")` + +6. **Summary**: + - Create analysis report saved to `output/reports/ocean_temp_analysis.md` + +### Example 6: Multi-Dataset Comparison +**User**: "Compare temperature datasets from two different organizations" + +**Agent Actions**: +1. **Setup**: `mkdir -p output/data output/plots output/reports` +2. Find both datasets using NDP tools +3. Download to `output/data/dataset1.csv` and `output/data/dataset2.csv` +4. Load both with `load_data` +5. Profile both with `profile_data` +6. Create comparison visualizations: + - `line_plot` → `output/plots/dataset1_trends.png` + - `line_plot` → `output/plots/dataset2_trends.png` + - `scatter_plot` → `output/plots/comparison_scatter.png` +7. Generate correlation analysis: + - `heatmap_plot` → `output/plots/dataset1_correlations.png` + - `heatmap_plot` → `output/plots/dataset2_correlations.png` +8. Create comparison report → `output/reports/dataset_comparison.md` + +## Tool Selection Guidelines + +**Use NDP Tools when**: +- Searching for datasets +- Discovering data sources +- Getting metadata and download URLs +- Exploring what data is available + +**Use Pandas Tools when**: +- Loading downloaded datasets +- Analyzing data structure and quality +- Computing statistics +- Transforming or filtering data + +**Use Plot Tools when**: +- Creating visualizations +- Exploring relationships +- Generating publication-ready figures +- Presenting results + +## Best Practices for Full Workflow + +1. **Always start with NDP discovery** - Don't analyze data you haven't found yet +2. **Create output directory structure** - `mkdir -p output/data output/plots output/reports` at project root +3. **Save everything to output/** - All files, plots, and reports go in the organized output structure +4. **Get dataset details first** - Understand format and structure before downloading +5. **Download to output/data/** - Keep all datasets organized in one location +6. **Profile before analyzing** - Use `profile_data` to understand data quality +7. **Visualize with output paths** - Always specify `output_path="output/plots/.png"` for plots +8. **Create summary reports** - Save analysis summaries to `output/reports/` for documentation +9. **Use descriptive filenames** - Name files clearly: `ocean_temp_2020_2024.csv`, not `data.csv` +10. **Provide complete guidance** - Tell user exact paths for all inputs and outputs diff --git a/agents/ndp-dataset-curator.md b/agents/ndp-dataset-curator.md new file mode 100644 index 0000000..572a9d0 --- /dev/null +++ b/agents/ndp-dataset-curator.md @@ -0,0 +1,185 @@ +--- +description: Specialized agent for dataset curation, metadata validation, and NDP publishing workflows +capabilities: + - Metadata quality assessment + - Dataset organization recommendations + - Publishing workflow guidance + - Resource format validation +mcp_tools: + - list_organizations + - search_datasets + - get_dataset_details +--- + +# NDP Dataset Curator + +Expert in dataset curation, metadata best practices, and NDP publishing workflows. + +You have access to three MCP tools for examining existing datasets and organizational structure in NDP: + +## Available MCP Tools + +### 1. `list_organizations` +Lists organizations in NDP. Use this to: +- Understand organizational structure +- Find examples of well-organized data providers +- Verify organization naming conventions +- Guide users on organization selection + +**Parameters**: +- `name_filter` (optional): Filter by name substring +- `server` (optional): 'global' (default), 'local', or 'pre_ckan' + +**Usage for Curation**: Examine how established organizations structure their data presence. + +### 2. `search_datasets` +Searches datasets by various criteria. Use this to: +- Find example datasets with good metadata +- Identify metadata patterns and standards +- Review resource format distribution +- Analyze dataset organization practices + +**Key Parameters**: +- `owner_org`: Study datasets from specific organizations +- `resource_format`: Examine format usage patterns +- `limit`: Control number of examples to review + +**Usage for Curation**: Pull example datasets to demonstrate metadata best practices. + +### 3. `get_dataset_details` +Retrieves complete dataset metadata. Use this to: +- Perform detailed metadata quality assessment +- Evaluate completeness of metadata fields +- Check resource documentation quality +- Identify metadata gaps and issues +- Provide specific improvement recommendations + +**Parameters**: +- `dataset_identifier`: Dataset ID or name +- `identifier_type`: 'id' (default) or 'name' +- `server`: 'global' (default) or 'local' + +**Usage for Curation**: Deep-dive analysis of metadata quality, format compliance, documentation completeness. + +## Expertise + +- **Metadata Standards**: Ensure datasets follow CKAN and scientific metadata conventions +- **Organization Management**: Guide dataset organization and categorization +- **Resource Validation**: Verify resource formats, accessibility, and documentation +- **Publishing Workflows**: Help prepare datasets for NDP publication + +## When to Invoke + +Use this agent when you need help with: +- Preparing datasets for NDP publication +- Validating metadata completeness and quality +- Organizing datasets within NDP structure +- Understanding CKAN metadata requirements +- Reviewing dataset documentation + +## Metadata Quality Assessment Workflow + +1. **Get Dataset Details**: Use `get_dataset_details` to retrieve complete metadata +2. **Evaluate Completeness**: Check for required and recommended CKAN fields +3. **Assess Documentation**: Review descriptions, tags, and resource documentation +4. **Validate Formats**: Verify resource formats are correct and standardized +5. **Compare Best Practices**: Use `search_datasets` to find exemplary datasets +6. **Provide Recommendations**: Specific, actionable improvements with examples + +## CKAN Metadata Fields to Validate + +### Required Fields +- **Title**: Clear, descriptive, not redundant with organization name +- **Description**: Comprehensive, well-formatted, includes methodology +- **Organization**: Appropriate organization assignment +- **Resources**: At least one resource with valid format and URL + +### Recommended Fields +- **Tags**: Relevant keywords for discoverability +- **Author/Maintainer**: Contact information +- **License**: Clear licensing information +- **Temporal Coverage**: Date ranges for time-series data +- **Spatial Coverage**: Geographic extent +- **Version**: Dataset version information + +### Resource Validation +- **Format**: Standardized format names (CSV, JSON, NetCDF, HDF5, GeoTIFF) +- **Description**: Clear explanation of resource contents +- **URL**: Accessible download links +- **Size**: File size information when available + +## MCP Tool Usage Best Practices + +- **Get full details** before assessment: Always use `get_dataset_details` first +- **Find exemplars**: Use `search_datasets` to locate well-documented datasets as examples +- **Study organizational patterns**: Use `list_organizations` to understand naming and structure +- **Provide specific examples**: Reference actual NDP datasets when recommending improvements +- **Validate across servers**: Check both global and local for comprehensive validation + +## Example Interactions with MCP Tool Usage + +### Example 1: Metadata Completeness Review +**User**: "Review dataset ID 'climate-temps-2023' for metadata completeness" + +**Agent Actions**: +1. Call `get_dataset_details(dataset_identifier="climate-temps-2023")` +2. Evaluate all metadata fields against CKAN standards +3. Check resource completeness (formats, descriptions, URLs) +4. Compare with similar high-quality datasets using `search_datasets(search_terms=["climate"], limit=5)` +5. Provide detailed report with specific missing/incomplete fields +6. Recommend improvements with examples from best-practice datasets + +### Example 2: Organization Selection Guidance +**User**: "Help me choose the right organization for my oceanographic dataset" + +**Agent Actions**: +1. Call `list_organizations(name_filter="ocean")` +2. Call `list_organizations(name_filter="marine")` +3. For each relevant organization, call `search_datasets(owner_org="", limit=3)` to see their datasets +4. Evaluate organizational focus, dataset types, and quality standards +5. Recommend best-fit organization with rationale +6. Provide examples of similar datasets in that organization + +### Example 3: Resource Format Validation +**User**: "Validate the resource formats and documentation for this dataset" + +**Agent Actions**: +1. Call `get_dataset_details(dataset_identifier="")` +2. Check each resource for: + - Standardized format names + - Complete descriptions + - Valid URLs + - Appropriate file types for data +3. Call `search_datasets(resource_format="NetCDF", limit=5)` to find examples of good resource documentation +4. Provide format-specific recommendations +5. Suggest improvements with examples from well-documented resources + +### Example 4: Publication Readiness Assessment +**User**: "Is my dataset ready for NDP publication? Dataset name: 'satellite-imagery-pacific'" + +**Agent Actions**: +1. Call `get_dataset_details(dataset_identifier="satellite-imagery-pacific", identifier_type="name")` +2. Perform comprehensive checklist: + - All required fields present + - Description quality and completeness + - Tags appropriate and sufficient + - Resources properly formatted + - Contact information provided + - License clearly stated +3. Call `search_datasets(search_terms=["satellite"], resource_format="GeoTIFF", limit=3)` for comparison +4. Provide publication readiness score with specific gaps +5. Prioritized action items for publication preparation + +### Example 5: Best Practices Demonstration +**User**: "Show me examples of well-documented climate datasets" + +**Agent Actions**: +1. Call `search_datasets(search_terms=["climate"], limit=10)` +2. Call `get_dataset_details` for top 3 results with most complete metadata +3. Analyze their metadata structure: + - Description formatting and content + - Tag usage + - Resource organization + - Documentation completeness +4. Extract best practices and patterns +5. Provide template based on these examples diff --git a/commands/ndp-dataset-details.md b/commands/ndp-dataset-details.md new file mode 100644 index 0000000..acdb096 --- /dev/null +++ b/commands/ndp-dataset-details.md @@ -0,0 +1,142 @@ +--- +description: Retrieve detailed information about a specific NDP dataset +--- + +# NDP Dataset Details + +Get comprehensive metadata and resource information for a specific dataset. + +This command provides access to detailed dataset metadata through the NDP MCP. + +## Available MCP Tool + +### `get_dataset_details` +Retrieves complete information for a specific dataset: + +**Parameters**: +- **dataset_identifier** (required): The dataset ID or name + - ID: Unique identifier (e.g., "a1b2c3d4-5678-90ef-ghij-klmnopqrstuv") + - Name: Human-readable name (e.g., "noaa-climate-temp-2023") +- **identifier_type** (optional): Type of identifier + - `'id'` (default) - Use when providing dataset ID + - `'name'` - Use when providing dataset name/slug +- **server** (optional): Server to query + - `'global'` (default) - Global NDP server + - `'local'` - Local/institutional server + +**Returns**: Comprehensive dataset information including: +- **Metadata**: Title, description, organization, tags, license +- **Resources**: All files/URLs with formats, sizes, descriptions +- **Temporal Info**: Creation date, last modified, temporal coverage +- **Spatial Info**: Geographic coverage (if applicable) +- **Contact Info**: Author, maintainer information +- **Additional Fields**: Custom metadata, processing info + +## Usage Patterns + +### After Dataset Search +``` +"Get details for dataset ID 'climate-temps-2023'" +``` +Uses: `get_dataset_details(dataset_identifier="climate-temps-2023", identifier_type="id")` + +### By Dataset Name +``` +"Show me all information about the 'ocean-temperature-pacific' dataset" +``` +Uses: `get_dataset_details(dataset_identifier="ocean-temperature-pacific", identifier_type="name")` + +### Resource Information +``` +"What formats are available for this dataset?" (after finding it in search) +``` +Uses: `get_dataset_details(dataset_identifier="")` + +### Quality Assessment +``` +"Review the metadata quality for dataset 'satellite-imagery-2024'" +``` +Uses: `get_dataset_details(dataset_identifier="satellite-imagery-2024", identifier_type="name")` + +## Information Retrieved + +### Core Metadata +- **Title**: Dataset name +- **Description**: Detailed description with methodology +- **Organization**: Owner organization +- **Tags**: Keywords for discoverability +- **License**: Usage rights and restrictions + +### Resource Details +For each resource (file/URL): +- **Format**: File format (CSV, JSON, NetCDF, HDF5, etc.) +- **URL**: Download link +- **Description**: Resource-specific description +- **Size**: File size (if available) +- **Created/Modified**: Timestamps + +### Additional Information +- **Author/Maintainer**: Contact information +- **Temporal Coverage**: Date ranges +- **Spatial Coverage**: Geographic extent +- **Version**: Dataset version +- **Related Datasets**: Links to related data +- **Processing Info**: Data processing details + +## When to Use + +1. **After Search**: Follow up on interesting datasets from search results +2. **Before Download**: Verify dataset contents and formats +3. **Quality Review**: Check metadata completeness for curation +4. **Citation Info**: Get complete information for proper attribution +5. **Resource Selection**: Choose specific files/formats from dataset +6. **Metadata Validation**: Assess dataset documentation quality + +## Workflow Integration + +1. **Search First**: Use `/ndp-search` to find datasets +2. **Get IDs**: Note dataset IDs or names from search results +3. **Retrieve Details**: Use this command for complete information +4. **Download**: Use resource URLs from details for data access + +## Example Interactions + +### Example 1: Complete Dataset Review +``` +User: "Get complete information for dataset ID 'abc123-climate'" +Claude uses: get_dataset_details(dataset_identifier="abc123-climate") +Result: Full metadata, all resources, download URLs, temporal/spatial coverage +``` + +### Example 2: Resource Exploration +``` +User: "What files are included in the NOAA temperature dataset?" +Claude uses: + 1. search_datasets(owner_org="NOAA", search_terms=["temperature"]) + 2. get_dataset_details(dataset_identifier="") +Result: List of all resources with formats and descriptions +``` + +### Example 3: Metadata Quality Check +``` +User: "Review the documentation for this oceanographic dataset" +Claude uses: get_dataset_details(dataset_identifier="") +Analysis: Evaluates description, tags, resource documentation, contact info +``` + +### Example 4: Multi-Dataset Comparison +``` +User: "Compare the resources available in these three datasets" +Claude uses: get_dataset_details() for each dataset +Result: Side-by-side comparison of formats, sizes, documentation +``` + +## Tips + +- **Use IDs when available**: More reliable than names +- **Check both servers**: Same dataset name might exist on multiple servers +- **Review all resources**: Datasets often have multiple files/formats +- **Note download URLs**: Save resource URLs for data access +- **Check temporal coverage**: Ensure data covers your time period of interest +- **Verify formats**: Confirm file formats are compatible with your tools +- **Read descriptions carefully**: Important processing details often in descriptions diff --git a/commands/ndp-organizations.md b/commands/ndp-organizations.md new file mode 100644 index 0000000..f94e6ee --- /dev/null +++ b/commands/ndp-organizations.md @@ -0,0 +1,110 @@ +--- +description: List and filter organizations in the National Data Platform +--- + +# NDP Organizations + +List all organizations contributing data to the National Data Platform. + +This command provides access to organization discovery functionality through the NDP MCP. + +## Available MCP Tool + +### `list_organizations` +Lists all organizations in NDP with optional filtering: + +**Parameters**: +- **name_filter** (optional): Filter organizations by name substring match + - Case-insensitive partial matching + - Example: "climate" matches "Climate Research Center", "NOAA Climate Lab" +- **server** (optional): Server to query + - `'global'` (default) - Public global NDP server + - `'local'` - Local/institutional NDP server + - `'pre_ckan'` - Pre-production server + +**Returns**: List of organization names and metadata including: +- Total count of organizations +- Organization names matching filter +- Server queried + +## Usage Patterns + +### Discover All Organizations +``` +"List all organizations in the National Data Platform" +``` +Uses: `list_organizations()` - No filter, returns all organizations + +### Filter by Keyword +``` +"Show me all organizations with 'climate' in their name" +``` +Uses: `list_organizations(name_filter="climate")` + +### Multi-Server Query +``` +"Compare organizations on global and local servers" +``` +Uses: `list_organizations(server="global")` and `list_organizations(server="local")` + +### Research-Specific Discovery +``` +"Find organizations related to oceanographic research" +``` +Uses: `list_organizations(name_filter="ocean")` and `list_organizations(name_filter="marine")` + +## Why Use This Command + +1. **Verify Organization Names**: Get exact names before using in dataset searches +2. **Explore Data Sources**: Understand what organizations contribute to NDP +3. **Guide Searches**: Identify relevant organizations for your research domain +4. **Server Comparison**: See organizational differences between servers +5. **Data Coverage**: Understand breadth of data providers + +## Workflow Integration + +1. **Start Here**: Use this command before searching datasets +2. **Identify Providers**: Find organizations relevant to your research +3. **Use in Search**: Pass organization names to `search_datasets` +4. **Iterate**: Refine organization filters as needed + +## Example Interactions + +### Example 1: General Exploration +``` +User: "List all organizations available on the local NDP server" +Claude uses: list_organizations(server="local") +Result: Complete list of local organizations with count +``` + +### Example 2: Targeted Discovery +``` +User: "Find organizations related to satellite data" +Claude uses: list_organizations(name_filter="satellite") +Result: Organizations with "satellite" in their name +``` + +### Example 3: Multi-Keyword Search +``` +User: "Show me organizations working on Earth observation" +Claude uses: + - list_organizations(name_filter="earth") + - list_organizations(name_filter="observation") +Result: Combined results from both searches +``` + +### Example 4: Before Dataset Search +``` +User: "I want to search for NOAA climate data" +Claude uses: list_organizations(name_filter="noaa") +Result: Exact NOAA organization name(s) +Then: Can proceed with search_datasets(owner_org="") +``` + +## Tips + +- **Use partial names**: "ocean" will match "Oceanographic Institute", "Ocean Research Lab", etc. +- **Try variations**: Search both "climate" and "atmospheric" to find all relevant organizations +- **Check both servers**: Global and local may have different organizations +- **Verify before searching**: Always confirm organization name before using in dataset searches +- **Multiple keywords**: Try related terms to discover all relevant providers diff --git a/commands/ndp-search.md b/commands/ndp-search.md new file mode 100644 index 0000000..bc82973 --- /dev/null +++ b/commands/ndp-search.md @@ -0,0 +1,89 @@ +--- +description: Search for datasets in the National Data Platform +--- + +# NDP Dataset Search + +Search for datasets across the National Data Platform ecosystem with advanced filtering options. + +This command provides access to the NDP MCP tools for dataset discovery and exploration. + +## Available MCP Tools + +When you use this command, Claude can invoke these MCP tools: + +### `search_datasets` - Primary search tool +Searches for datasets using various criteria: +- **search_terms**: List of terms to search across all fields +- **owner_org**: Filter by organization name +- **resource_format**: Filter by format (CSV, JSON, NetCDF, HDF5, GeoTIFF, etc.) +- **dataset_description**: Search in descriptions +- **server**: Query 'global' (default) or 'local' server +- **limit**: Maximum results (default: 20) + +### `list_organizations` - Organization discovery +Lists available organizations: +- **name_filter**: Filter by name substring +- **server**: Query 'global' (default), 'local', or 'pre_ckan' + +### `get_dataset_details` - Detailed information +Retrieves complete metadata for a specific dataset: +- **dataset_identifier**: Dataset ID or name from search results +- **identifier_type**: 'id' (default) or 'name' +- **server**: 'global' (default) or 'local' + +## Recommended Workflow + +1. **Discover Organizations**: Use `list_organizations` to find relevant data sources +2. **Search Datasets**: Use `search_datasets` with appropriate filters +3. **Review Results**: Claude will summarize matching datasets +4. **Get Details**: Use `get_dataset_details` for datasets of interest +5. **Refine Search**: Adjust filters based on results + +## Best Practices + +- **Always verify organization names** with `list_organizations` before using in search +- **Start broad, then refine**: Begin with simple terms, add filters as needed +- **Limit results appropriately**: Default 20 is good, increase if needed +- **Use format filters**: Narrow to specific formats (NetCDF, CSV, etc.) when relevant +- **Multi-server searches**: Query both global and local for comprehensive coverage + +## Example Queries + +### Basic Search +``` +"Find climate datasets from NOAA" +``` +Expected tools: `list_organizations(name_filter="noaa")`, then `search_datasets(owner_org="NOAA", search_terms=["climate"])` + +### Format-Specific Search +``` +"Search for oceanographic data in NetCDF format" +``` +Expected tools: `search_datasets(search_terms=["oceanographic"], resource_format="NetCDF")` + +### Organization-Based Search +``` +"List all datasets from a specific research institution" +``` +Expected tools: `list_organizations(name_filter="")`, then `search_datasets(owner_org="")` + +### Refined Search with Limit +``` +"Find CSV datasets about temperature monitoring, limit to 10 results" +``` +Expected tools: `search_datasets(search_terms=["temperature", "monitoring"], resource_format="CSV", limit=10)` + +### Multi-Server Comparison +``` +"Compare oceanographic datasets on global and local servers" +``` +Expected tools: `search_datasets(server="global", ...)` and `search_datasets(server="local", ...)` + +## Tips for Effective Searching + +1. **Use specific terminology**: Scientific terms work better than generic ones +2. **Combine filters**: Organization + format + terms = precise results +3. **Check multiple formats**: Try CSV, NetCDF, HDF5 for scientific data +4. **Explore organizations first**: Understanding data providers helps target searches +5. **Request details selectively**: Full metadata for only the most relevant datasets diff --git a/hooks/hooks.json b/hooks/hooks.json new file mode 100644 index 0000000..fbd6e71 --- /dev/null +++ b/hooks/hooks.json @@ -0,0 +1,77 @@ +{ + "hooks": { + "UserPromptSubmit": [ + { + "matcher": "", + "hooks": [ + { + "type": "command", + "command": "${CLAUDE_PLUGIN_ROOT}/hooks/log_ndp_events.py --event-type UserPromptSubmit" + } + ] + } + ], + "PreToolUse": [ + { + "matcher": "ndp", + "hooks": [ + { + "type": "command", + "command": "${CLAUDE_PLUGIN_ROOT}/hooks/log_ndp_events.py --event-type PreToolUse" + } + ] + }, + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "echo \"$(date +%s.%N),$(ps -o %cpu= -p $$),$(ps -o rss= -p $$),$CLAUDE_TOOL_NAME,start\" >> ~/.claude/performance.csv" + } + ] + } + ], + "PostToolUse": [ + { + "matcher": "ndp", + "hooks": [ + { + "type": "command", + "command": "${CLAUDE_PLUGIN_ROOT}/hooks/log_ndp_events.py --event-type PostToolUse" + } + ] + }, + { + "matcher": "*", + "hooks": [ + { + "type": "command", + "command": "echo \"$(date +%s.%N),$(ps -o %cpu= -p $$),$(ps -o rss= -p $$),$CLAUDE_TOOL_NAME,end\" >> ~/.claude/performance.csv; if [[ $(wc -l < ~/.claude/performance.csv) -gt 1000 ]]; then tail -n 500 ~/.claude/performance.csv > ~/.claude/performance.csv.tmp && mv ~/.claude/performance.csv.tmp ~/.claude/performance.csv; fi" + } + ] + } + ], + "SessionStart": [ + { + "matcher": "", + "hooks": [ + { + "type": "command", + "command": "${CLAUDE_PLUGIN_ROOT}/hooks/log_ndp_events.py --event-type SessionStart" + } + ] + } + ], + "Stop": [ + { + "matcher": "", + "hooks": [ + { + "type": "command", + "command": "${CLAUDE_PLUGIN_ROOT}/hooks/log_ndp_events.py --event-type Stop" + } + ] + } + ] + } +} diff --git a/hooks/log_ndp_events.py b/hooks/log_ndp_events.py new file mode 100755 index 0000000..a83405d --- /dev/null +++ b/hooks/log_ndp_events.py @@ -0,0 +1,159 @@ +#!/usr/bin/env -S uv run --python 3.10 --script +# /// script +# requires-python = ">=3.10" +# /// +""" +NDP Plugin Event Logger +Logs Claude Code events related to NDP plugin usage to a local file. +Enhanced to capture tool names, user input, and agent responses. +""" + +import json +import sys +import os +import argparse +from datetime import datetime +from pathlib import Path + +def get_log_file_path(): + """Get the log file path within plugin directory""" + # Get plugin root directory + plugin_root = Path(__file__).parent.parent + logs_dir = plugin_root / "logs" + + # Create logs directory if it doesn't exist + logs_dir.mkdir(exist_ok=True) + + return logs_dir / "ndp_events.log" + +def extract_enhanced_data(event_type: str, event_data: dict) -> dict: + """Extract enhanced information from event data""" + enhanced = { + "timestamp": datetime.now().isoformat(), + "event_type": event_type, + "session_id": event_data.get("session_id", "unknown"), + } + + # Extract tool information for PreToolUse and PostToolUse + if event_type in ["PreToolUse", "PostToolUse"]: + tool_data = event_data.get('tool', {}) + if tool_data: + enhanced['tool_name'] = tool_data.get('name', 'unknown') + enhanced['tool_input'] = tool_data.get('input', {}) + + # For PostToolUse, capture tool results + if event_type == "PostToolUse": + if 'result' in event_data: + enhanced['tool_result'] = event_data['result'] + if 'output' in event_data: + enhanced['tool_output'] = event_data['output'] + if 'error' in event_data: + enhanced['tool_error'] = event_data['error'] + + # Extract user input for UserPromptSubmit + if event_type == "UserPromptSubmit": + if 'text' in event_data: + enhanced['user_prompt'] = event_data['text'] + if 'messages' in event_data: + enhanced['conversation_messages'] = event_data['messages'] + + # For PostToolUse, extract agent response from transcript + if event_type == "PostToolUse" and 'transcript_path' in event_data: + transcript_path = event_data['transcript_path'] + if os.path.exists(transcript_path): + try: + # Read last few messages to capture recent agent response + recent_chat = [] + with open(transcript_path, 'r') as f: + lines = f.readlines() + # Get last 5 messages to capture context + for line in lines[-5:]: + line = line.strip() + if line: + try: + msg = json.loads(line) + recent_chat.append(msg) + except json.JSONDecodeError: + pass + + enhanced['recent_chat'] = recent_chat + + # Extract the latest agent response + for msg in reversed(recent_chat): + if msg.get('role') == 'assistant': + enhanced['latest_agent_response'] = msg.get('content', []) + break + + except Exception as e: + enhanced['transcript_read_error'] = str(e) + + # For Stop event, optionally include full chat if requested + if event_type == "Stop" and 'transcript_path' in event_data: + transcript_path = event_data['transcript_path'] + if os.path.exists(transcript_path): + try: + chat_data = [] + with open(transcript_path, 'r') as f: + for line in f: + line = line.strip() + if line: + try: + chat_data.append(json.loads(line)) + except json.JSONDecodeError: + pass + + # Add summary statistics + enhanced['chat_summary'] = { + 'total_messages': len(chat_data), + 'user_messages': sum(1 for msg in chat_data if msg.get('role') == 'user'), + 'assistant_messages': sum(1 for msg in chat_data if msg.get('role') == 'assistant'), + } + # Optionally include last few messages + enhanced['last_5_messages'] = chat_data[-5:] if chat_data else [] + + except Exception as e: + enhanced['chat_read_error'] = str(e) + + # Include raw event data for completeness + enhanced['raw_data'] = event_data + + return enhanced + +def log_event(event_type: str, event_data: dict): + """Log event to file with enhanced data extraction""" + try: + log_file = get_log_file_path() + + # Prepare enhanced log entry + log_entry = extract_enhanced_data(event_type, event_data) + + # Append to log file (one JSON object per line) + with open(log_file, "a") as f: + 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