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Optimize LLM Cost Latency

Agent skill
1 skill

Cuts LLM token cost and tail latency via context trimming, provider prompt caching on stable prefixes, model tiering/routing, semantic answer caching, batch APIs, and streaming, proving a measured before/after on cost-per-request and p50/p95 at equal output quality.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryEngineeringStars0

About this skill

Cuts LLM token cost and tail latency via context trimming, provider prompt caching on stable prefixes, model tiering/routing, semantic answer caching, batch APIs, and streaming, proving a measured before/after on cost-per-request and p50/p95 at equal output quality.

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
Review the source before using this skill

This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

Automated security scan: Partial

Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.

0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: fc037da8d6c8e3d460b9ea729ebc0ed33158c2e4943c080b364cdcadaccfc975

About scan coverage and limitations

About this listing

Category
Engineering
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Optimize LLM Cost Latency | Agent Skills Atlas