Agent skill
palantir-hello-world
Create a minimal working Palantir Foundry example querying Ontology objects. Use when starting a new Foundry integration, testing your setup, or learning basic Foundry API and Ontology patterns. Trigger with phrases like "palantir hello world", "palantir example", "palantir quick start", "foundry first query".
Install this agent skill to your Project
npx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/main/plugins/saas-packs/palantir-pack/skills/palantir-hello-world
SKILL.md
Palantir Hello World
Overview
Build a minimal working example that connects to Palantir Foundry, queries Ontology objects via the REST API, reads a dataset, and applies an action. Uses real foundry-platform-sdk Python API calls.
Prerequisites
- Completed
palantir-install-authsetup - Valid bearer token or OAuth2 credentials
- At least one Ontology with object types configured in your Foundry enrollment
Instructions
Step 1: List Available Ontologies
import os
import foundry
client = foundry.FoundryClient(
auth=foundry.UserTokenAuth(
hostname=os.environ["FOUNDRY_HOSTNAME"],
token=os.environ["FOUNDRY_TOKEN"],
),
hostname=os.environ["FOUNDRY_HOSTNAME"],
)
# List all ontologies you have access to
for ont in client.ontologies.Ontology.list():
print(f"Ontology: {ont.api_name} RID: {ont.rid}")
Step 2: Query Ontology Objects
# List objects of type "Employee" from the default ontology
# The object type api_name comes from your Ontology configuration
ONTOLOGY = "your-ontology-api-name"
OBJECT_TYPE = "Employee"
objects = client.ontologies.OntologyObject.list(
ontology=ONTOLOGY,
object_type=OBJECT_TYPE,
page_size=5,
)
for obj in objects.data:
props = obj.properties
print(f" {props.get('fullName', 'N/A')} — {props.get('department', 'N/A')}")
Step 3: Get a Single Object by Primary Key
employee = client.ontologies.OntologyObject.get(
ontology=ONTOLOGY,
object_type=OBJECT_TYPE,
primary_key="EMP-001",
)
print(f"Found: {employee.properties}")
Step 4: Read a Dataset
# Read rows from a Foundry dataset (tabular)
DATASET_RID = "ri.foundry.main.dataset.xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
# Get dataset metadata
dataset = client.datasets.Dataset.get(dataset_rid=DATASET_RID)
print(f"Dataset: {dataset.name}, Path: {dataset.path}")
# Read rows from the dataset (CSV format)
content = client.datasets.Dataset.read(
dataset_rid=DATASET_RID,
branch_id="master",
format="arrow", # or "csv"
)
print(f"Read {len(content)} bytes of data")
Step 5: Apply an Ontology Action
# Actions modify objects — e.g., updating an employee's department
result = client.ontologies.Action.apply(
ontology=ONTOLOGY,
action_type="updateDepartment",
parameters={
"employeeId": "EMP-001",
"newDepartment": "Engineering",
},
)
print(f"Action result: {result.validation}")
Step 6: Run and Verify
set -euo pipefail
python hello_foundry.py
# Expected output:
# Ontology: my-company RID: ri.ontology.main.ontology.xxx
# Employee: Jane Doe — Engineering
# Action result: VALID
Output
- Authenticated connection to Palantir Foundry
- Listed ontologies and object types
- Retrieved objects with property values
- Read dataset content
- Applied an action to modify an object
Error Handling
| Error | Cause | Solution |
|---|---|---|
ObjectTypeNotFound |
Wrong api_name |
Check Ontology Manager for exact object type names |
ObjectNotFound |
Invalid primary key | Verify the key exists; keys are case-sensitive |
ActionValidationFailed |
Missing required params | Check action definition for required parameters |
DatasetNotFound |
Wrong RID or no access | Verify RID in Foundry UI; check project permissions |
401 Unauthorized |
Token expired | Regenerate in Developer Console |
Examples
Using the REST API Directly (curl)
# List objects via REST
curl -s -H "Authorization: Bearer $FOUNDRY_TOKEN" \
"https://$FOUNDRY_HOSTNAME/api/v2/ontologies/my-ontology/objects/Employee?pageSize=5" \
| python -m json.tool
TypeScript OSDK Equivalent
import { createClient } from "@osdk/client";
import { Employee } from "@my-app/sdk"; // generated from OSDK
const employees = await client(Employee)
.where({ department: "Engineering" })
.fetchPage({ pageSize: 10 });
employees.data.forEach(emp => console.log(emp.fullName));
Resources
Next Steps
- Set up iterative development:
palantir-local-dev-loop - Build data pipelines with transforms:
palantir-core-workflow-a - Query and link objects:
palantir-core-workflow-b
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
dockerfile-generator
Dockerfile Generator - Auto-activating skill for DevOps Basics. Triggers on: dockerfile generator, dockerfile generator Part of the DevOps Basics skill category.
branch-naming-helper
Branch Naming Helper - Auto-activating skill for DevOps Basics. Triggers on: branch naming helper, branch naming helper Part of the DevOps Basics skill category.
readme-generator
Readme Generator - Auto-activating skill for DevOps Basics. Triggers on: readme generator, readme generator Part of the DevOps Basics skill category.
makefile-generator
Makefile Generator - Auto-activating skill for DevOps Basics. Triggers on: makefile generator, makefile generator Part of the DevOps Basics skill category.
gitignore-generator
Gitignore Generator - Auto-activating skill for DevOps Basics. Triggers on: gitignore generator, gitignore generator Part of the DevOps Basics skill category.
pre-commit-hook-setup
Pre Commit Hook Setup - Auto-activating skill for DevOps Basics. Triggers on: pre commit hook setup, pre commit hook setup Part of the DevOps Basics skill category.
Didn't find tool you were looking for?