AI & Agents
Effective context engineering for AI agents
Last updated 2026-07-26 · benchmark measured 2026-07-26 — deterministic & reproducible
Anthropic's guide to context engineering for AI agents using Claude.
Is Effective context engineering for AI agents production-ready?
Legit.Show scores Effective context engineering for AI agents 86 out of 100 — the simple average of its 7 measured frames. Legit.Show ran its deterministic 7-Frame production-readiness benchmark on Effective context engineering for AI agents (public-surface assessment), measured from the public surface with no LLM in the scoring path. Its strongest frame is Privacy; its weakest is Security. Every frame it averages is published with its evidence on the Legit.Show listing.
The 7 Frames
- Performance — 72/100
- Accessibility — 96/100
- Security — 65/100
- Privacy — 100/100
- Reliability — 100/100
- Standards — 86/100
- Discoverability — 85/100
What we measured
- Security headers present: CSP, HSTS, X-Frame-Options.
- Served over HTTPS with a valid certificate.
- Real Lighthouse performance run — 59 ms to first byte.
- Returns a proper 404 for unknown routes.
- 3 of 3 sampled routes reachable.
- Has a reachable privacy policy.
- Sets cookies / loads scripts with no consent prompt.
- Discoverable: sitemap, OpenGraph image, canonical URL.
Who built it
product account @AnthropicAI
Who it's for
AI engineers · LLM developers · AI agent builders · ML practitioners · Enterprise teams
Pricing
Free to read
Visit Effective context engineering for AI agents → · How this was measured →