Agent skill · software engineering · jeremylongshore
ramp-cost-tuning
Reduce Ramp integration workload and operating cost without losing financial completeness. Use when polling, storage, retries, or accounting synchronization consumes excessive capacity. Trigger with "optimize Ramp sync cost" or "reduce Ramp API calls".
Why this skill is useful
Provides specific API integration patterns for Ramp's corporate card management that the AI wouldn't reliably generate on its own.
What it needs
Requires ramp account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Ramp Integration Cost and Workload Tuning Overview Cost tuning is a correctness exercise: remove redundant retrieval, not evidence. Establish a complete baseline, shift change detection to webhooks where supported, and preserve periodic reconciliation for missed or non-evented changes. Prerequisites Identify the Ramp application, environment, business entities, affected data and workflows, accountable owner, and rollback boundary. Read references/official-docs.md and re-check endpoint schemas, scopes, limits, and support status before a live operation. Use synthetic fixtures or Ramp sandbox until production access and business effects are explicitly approved. Prepare approved secret storage and a sanitized evidence location. Current Contract Ramp recommends persisting an initial full sync locally and fetching new or changed records incrementally where endpoint semantics support it. Incremental filters are endpoint-specific; for example, transaction syncedafter covers accounting sync events, not every transaction update. Webhooks reduce polling but do not remove the need for idempotent consumption and periodic reconciliation. Batch and page limits are endpoint-specific and must be read from the current schema before tuning. Instructions 1. Measure requests, pages, transferred bytes, retries, storage growth, reconciliation lag, webhook volume, and operator toil by endpoint and entity. 2. Classify each poll as initial seed, supported incremental read, unsupported change detection, recovery reconciliation, or waste. 3. Replace eligible near-real-time polling with scoped webhooks and a durable deduplicating queue; retain scheduled reconciliation for gaps. 4. Use maximum safe page sizes, endpoint filters with verified semantics, bounded concurrency, conditional local reads, and batch operations where documented. 5. Compare pre/post completeness, latency, error rate, API demand, infrastructure cost, and recovery time before accepting the change. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/ramp-cost-tuning