OP

openevidence-performance-tuning

Improves latency for OpenEvidence clinical queries through strategic caching and citation batching.

Install

mkdir -p .claude/skills/openevidence-performance-tuning && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4797" && unzip -o skill.zip -d .claude/skills/openevidence-performance-tuning && rm skill.zip

Installs to .claude/skills/openevidence-performance-tuning

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Performance Tuning for OpenEvidence.
36 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Cache evidence responses with a 30-minute TTL
  • →Cache citation metadata with a 1-hour TTL
  • →Batch citation retrieval in groups of 25 with 500ms pauses
  • →Enable HTTP keep-alive for persistent API connections
  • →Monitor average query latency
  • →Set client timeout to 30s for complex multi-condition queries

How it works

The skill implements caching strategies for evidence summaries and citation batching to reduce system load. It optimizes query specificity and request handling for large-scale medical data retrieval.

Inputs & outputs

You give it
Clinical API queries for evidence and citations
You get back
Optimized clinical query performance and reduced response times

When to use openevidence-performance-tuning

  • →Implement response caching for medical evidence queries
  • →Batch citation fetches to reduce API overhead
  • →Optimize query performance for clinical AI tools
  • →Set TTL intervals for evidence and citation data

About this skill

OpenEvidence Prompt Refinement

Overview

Tune context and question structure while holding clinical accountability and source review constant. 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

  • The official guide publishes prompt guidance and dedicated workflows for complex cases and Snow.
  • More detail is not always safer; include only relevant, authorized context.
  • Performance means decision usefulness and evidence traceability, not fastest answer or longest response.

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. State the decision, intended user, population, outcome, constraints, and what uncertainty must remain visible.
  2. Remove identifiers and irrelevant narrative; separate known facts from assumptions.
  3. Run a baseline synthetic or authorized de-identified question and score relevance, citations, applicability, and reviewer effort.
  4. Change one prompt element at a time: specificity, timeframe, comparator, output structure, or request for conflicting evidence.
  5. Open citations and have a qualified clinician compare versions using the same rubric.
  6. Save a reusable pattern only if it improves the defined outcome across multiple representative cases.

Approval Boundaries

Do not create or share accounts; change access, roles, agreements, consent, retention, or security settings; enter PHI; record a conversation; copy content into another system; contact a patient; make a diagnosis or treatment decision; submit billing; transmit a support packet; run a production pilot; or represent vendor capabilities without explicit approval from the accountable owner. A qualified professional remains responsible for clinical decisions.

Output

Return scope, current first-party evidence and date, data classification, workflow or findings, citations reviewed, assumptions rejected, clinical and governance owners, approval state, unresolved risk, and the exact next action. Redact patient and credential data.

Error Handling

ConditionResponse
Prompt becomes leadingRestore neutral framing and request alternatives or conflicting evidence.
Answer gets longer, not betterOptimize for reviewable claims and cited evidence.
Case is urgentUse the clinical emergency workflow, not prompt iteration.

Examples

This compact example shows the minimum reviewable handoff; adapt fields to the approved workflow without adding sensitive data.

Input:

decision=diagnostic workup; context=de-identified; variants=3; reviewer=clinician

Expected handoff:

best-variant=2; traceability=improved; uncertainty=preserved; template=approved

Resources

When not to use it

  • →When evidence summaries are stale due to a cache that is too long for rapidly evolving topics
  • →When a study is not yet indexed, resulting in missing citations

Limitations

  • →Slow evidence queries can occur with broad multi-condition searches
  • →Rate limits can be hit with too many parallel citation fetches
  • →Complex queries may time out if multi-study synthesis exceeds limits

How it compares

This skill explicitly defines TTLs for evidence and citations, batches citation fetches with pauses, and uses connection pooling, unlike generic performance tuning.

Compared to similar skills

openevidence-performance-tuning side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
openevidence-performance-tuning (this skill)12moNo flagsIntermediate
exa-performance-tuning32moReviewIntermediate
perplexity-rate-limits02moNo flagsIntermediate
documenso-performance-tuning02moReviewIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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