Agent skill · data analytics · jeremylongshore
palantir-cost-tuning
Reduce Foundry compute usage through measured engine, resource, incremental, schedule, and Compute Module decisions. Use when build or application usage is high or unpredictable. Trigger with "Foundry cost tuning" or "Palantir compute usage".
Why this skill is useful
Adds executable scripts for optimizing Palantir Foundry costs through incremental builds and usage monitoring that aren't in public docs.
What it needs
Requires palantir account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Palantir Compute and Usage Optimization Overview Optimize from measured Foundry usage and telemetry, not invented data-volume bands. Separate transform-build consumption from interactive Compute Module replica consumption because they have different controls and failure modes. Prerequisites Identify the pipeline, build jobs, Compute Modules, schedules, owners, service objectives, and current usage window. Capture build duration, requested and observed CPU/memory, queue time, input change rate, output volume, and module replica activity. Read references/official-docs.md and confirm contract-specific pricing or usage questions with the account owner or Palantir representative. Define correctness and latency constraints that cannot be traded away. Current Contract Python transforms can use single-node engines or Spark; required feature support constrains the choice. Foundry build metrics expose requested and observed CPU and memory, enabling evidence-based resource changes. Incremental transforms can reduce repeated work only when their transaction semantics remain correct. Compute Module usage is measured while replicas are starting or active, including predictive autoscaling behavior. Instructions 1. Build a baseline that separates transform jobs, schedules, previews, retries, snapshots, and Compute Module replicas. 2. Rank usage drivers by measured consumption and business criticality. 3. Test one change at a time: engine, resource request, incremental mode, schedule, batch shape, property selection, or replica policy. 4. Compare output parity, latency, failure rate, queue time, and consumption against the baseline. 5. Promote the smallest validated change and monitor one full representative operating window. Tool Discipline Use Glob to locate candidate repositories, manifests, configurations, and evidence without widening scope. Use Grep to find relevant identifiers, declarations, permissions, errors, and stale claims. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/palantir-cost-tuning--daca82