Pltr Cli
by anjor
Helps you work with Palantir Foundry using the pltr CLI. Use this when you need to query datasets, manage orchestration builds, work with ontologies, run SQL queries, manage folders/spaces/projects, copy datasets, or perform admin operations in Foundry. Triggers: Foundry, pltr, dataset, SQL query, ontology, build, schedule, RID.
Skill Details
Repository Files
19 files in this skill directory
name: pltr-cli description: Helps you work with Palantir Foundry using the pltr CLI. Use this when you need to query datasets, manage orchestration builds, work with ontologies, run SQL queries, manage folders/spaces/projects, copy datasets, or perform admin operations in Foundry. Triggers: Foundry, pltr, dataset, SQL query, ontology, build, schedule, RID.
pltr-cli: Palantir Foundry CLI
This skill helps you use the pltr-cli to interact with Palantir Foundry effectively.
Compatibility
- Skill version: 1.1.0
- pltr-cli version: 0.12.0+
- Python: 3.9, 3.10, 3.11, 3.12
- Dependencies: foundry-platform-sdk >= 1.69.0
Overview
pltr-cli is a comprehensive CLI with 100+ commands for:
- Dataset operations: Get info, list files, download files, manage branches and transactions
- SQL queries: Execute queries, export results, manage async queries
- Ontology: List ontologies, object types, objects, execute actions and queries
- Orchestration: Manage builds, jobs, and schedules
- Filesystem: Folders, spaces, projects, resources
- Admin: User, group, role management
- Connectivity: External connections and data imports
- MediaSets: Media file management
- Language Models: Interact with Anthropic Claude models and OpenAI embeddings
- Streams: Create and manage streaming datasets, publish real-time data
- Functions: Execute queries and inspect value types
- AIP Agents: Manage AI agents, sessions, and versions
- Models: ML model registry for model and version management
Critical Concepts
RID-Based API
The Foundry API is RID-based (Resource Identifier). Most commands require RIDs:
- Datasets:
ri.foundry.main.dataset.{uuid} - Folders:
ri.compass.main.folder.{uuid}(root:ri.compass.main.folder.0) - Builds:
ri.orchestration.main.build.{uuid} - Schedules:
ri.orchestration.main.schedule.{uuid} - Ontologies:
ri.ontology.main.ontology.{uuid}
Users must know RIDs in advance (from Foundry web UI or previous API calls).
Authentication
Before using any command, ensure authentication is configured:
# Configure interactively
pltr configure configure
# Or use environment variables
export FOUNDRY_TOKEN="your-token"
export FOUNDRY_HOST="foundry.company.com"
# Verify connection
pltr verify
Output Formats
All commands support multiple output formats:
pltr <command> --format table # Default: Rich table
pltr <command> --format json # JSON output
pltr <command> --format csv # CSV format
pltr <command> --output file.csv # Save to file
Profile Selection
Use --profile to switch between Foundry instances:
pltr <command> --profile production
pltr <command> --profile development
Reference Files
Load these files based on the user's task:
| Task Type | Reference File |
|---|---|
| Setup, authentication, getting started | reference/quick-start.md |
| Dataset operations (get, files, branches, transactions) | reference/dataset-commands.md |
| SQL queries | reference/sql-commands.md |
| Builds, jobs, schedules | reference/orchestration-commands.md |
| Ontologies, objects, actions | reference/ontology-commands.md |
| Users, groups, roles, orgs | reference/admin-commands.md |
| Folders, spaces, projects, resources, permissions | reference/filesystem-commands.md |
| Connections, imports | reference/connectivity-commands.md |
| Media sets, media items | reference/mediasets-commands.md |
| Anthropic Claude models, OpenAI embeddings | reference/language-models-commands.md |
| Streaming datasets, real-time data publishing | reference/streams-commands.md |
| Functions queries, value types | reference/functions-commands.md |
| AIP Agents, sessions, versions | reference/aip-agents-commands.md |
| ML model registry, model versions | reference/models-commands.md |
Workflow Files
For common multi-step tasks:
| Workflow | File |
|---|---|
| Data exploration, SQL analysis, ontology queries | workflows/data-analysis.md |
| ETL pipelines, scheduled jobs, data quality | workflows/data-pipeline.md |
| Setting up permissions, resource roles, access control | workflows/permission-management.md |
Common Commands Quick Reference
# Verify setup
pltr verify
# Current user info
pltr admin user current
# Execute SQL query
pltr sql execute "SELECT * FROM my_table LIMIT 10"
# Get dataset info
pltr dataset get ri.foundry.main.dataset.abc123
# List files in dataset
pltr dataset files list ri.foundry.main.dataset.abc123
# Download file from dataset
pltr dataset files get ri.foundry.main.dataset.abc123 "/path/file.csv" "./local.csv"
# Copy dataset to another folder
pltr cp ri.foundry.main.dataset.abc123 ri.compass.main.folder.target456
# List folder contents
pltr folder list ri.compass.main.folder.0 # root folder
# Search builds
pltr orchestration builds search
# Interactive shell mode
pltr shell
# Send message to Claude model
pltr language-models anthropic messages ri.language-models.main.model.xxx \
--message "Explain this concept"
# Generate embeddings
pltr language-models openai embeddings ri.language-models.main.model.xxx \
--input "Sample text"
# Create streaming dataset
pltr streams dataset create my-stream \
--folder ri.compass.main.folder.xxx \
--schema '{"fieldSchemaList": [{"name": "value", "type": "STRING"}]}'
# Publish record to stream
pltr streams stream publish ri.foundry.main.dataset.xxx \
--branch master \
--record '{"value": "hello"}'
# Execute a function query
pltr functions query execute myQuery --parameters '{"limit": 10}'
# Get AIP Agent info
pltr aip-agents get ri.foundry.main.agent.abc123
# List agent sessions
pltr aip-agents sessions list ri.foundry.main.agent.abc123
# Get ML model info
pltr models model get ri.foundry.main.model.abc123
# List model versions
pltr models version list ri.foundry.main.model.abc123
Best Practices
- Always verify authentication first: Run
pltr verifybefore starting work - Use appropriate output format: JSON for programmatic use, CSV for spreadsheets, table for readability
- Use async for large queries:
pltr sql submit+pltr sql waitfor long-running queries - Export results: Use
--outputto save results for further analysis - Use shell mode for exploration:
pltr shellprovides tab completion and history
Getting Help
pltr --help # All commands
pltr <command> --help # Command help
pltr <command> <sub> --help # Subcommand help
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