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Palantir Foundry CLI

Use the pltr CLI to query datasets, run SQL, manage builds, ontologies, projects, users, streams, AI agents, and ML models in Palantir Foundry.

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版本1.0.1
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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 TypeReference File
Setup, authentication, getting startedreference/quick-start.md
Dataset operations (get, files, branches, transactions)reference/dataset-commands.md
SQL queriesreference/sql-commands.md
Builds, jobs, schedulesreference/orchestration-commands.md
Ontologies, objects, actionsreference/ontology-commands.md
Users, groups, roles, orgsreference/admin-commands.md
Folders, spaces, projects, resources, permissionsreference/filesystem-commands.md
Connections, importsreference/connectivity-commands.md
Media sets, media itemsreference/mediasets-commands.md
Anthropic Claude models, OpenAI embeddingsreference/language-models-commands.md
Streaming datasets, real-time data publishingreference/streams-commands.md
Functions queries, value typesreference/functions-commands.md
AIP Agents, sessions, versionsreference/aip-agents-commands.md
ML model registry, model versionsreference/models-commands.md

Workflow Files

For common multi-step tasks:

WorkflowFile
Data exploration, SQL analysis, ontology queriesworkflows/data-analysis.md
ETL pipelines, scheduled jobs, data qualityworkflows/data-pipeline.md
Setting up permissions, resource roles, access controlworkflows/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

  1. Always verify authentication first: Run pltr verify before starting work
  2. Use appropriate output format: JSON for programmatic use, CSV for spreadsheets, table for readability
  3. Use async for large queries: pltr sql submit + pltr sql wait for long-running queries
  4. Export results: Use --output to save results for further analysis
  5. Use shell mode for exploration: pltr shell provides tab completion and history

Getting Help

pltr --help                    # All commands
pltr <command> --help          # Command help
pltr <command> <sub> --help    # Subcommand help

如何使用「Palantir Foundry CLI」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Palantir Foundry CLI」技能完成任务
  4. 结果即时呈现,支持继续对话优化

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