Agent skill · data analytics · jeremylongshore
openevidence-cost-tuning
Evaluate OpenEvidence adoption value and access burden without inventing prices, quotas, or usage telemetry. Use when working with OpenEvidence in a healthcare organization. Trigger with "openevidence cost tuning", "OpenEvidence value", or a matching workflow request.
Why this skill is useful
Provides specific optimization strategies and a usage tracking script for the OpenEvidence API that the AI wouldn't reliably generate on its own.
What it needs
Requires openevidence account access. About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
OpenEvidence Access and Value Review Overview Build a decision-ready value review from authorized local evidence and current commercial terms. Keep inputs minimal, separate observed facts from assumptions, and leave consequential decisions with the named accountable owner. Prerequisites A clearly bounded workflow, accountable clinical owner, and organizational policy Current first-party OpenEvidence documentation and applicable institution agreements Synthetic or properly authorized minimum-necessary data Tool Discipline Use Read, Glob, and Grep to inspect supplied policies, plans, and evidence. Use WebFetch only for current first-party OpenEvidence documentation. Use Write or Edit only when the user requests a named deliverable with an approved destination. Never expose credentials, PHI, recordings, or unrestricted environment output. Current Contract Public product pages do not establish institution-specific price, quota, SLA, or entitlement terms. Only a current order form, MSA, or authorized account surface can establish commercial commitments. Clinical quality and safety outcomes must not be reduced to raw query volume. Authentication Use only the official OpenEvidence web/mobile sign-in or an institution-approved access path. Do not invent API keys, OAuth clients, SDK credentials, service accounts, or private endpoints. Never ask a user to reveal a password, session token, cookie, or recovery code. Instructions 1. Define the decision: pilot continuation, feature expansion, workflow retirement, or contract review. 2. Collect authorized evidence for active users, completed workflows, time saved, failure modes, and training/support burden. 3. Separate product facts from institution-specific contract terms and unverified anecdotes. 4. Measure value by workflow outcome, evidence-review quality, clinician time, and adoption friction; avoid patient-outcome causality claims. 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/openevidence-cost-tuning