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AI & Agents

Effective context engineering for AI agents

Last updated 2026-07-26 · benchmark measured 2026-09-13 — deterministic & reproducible

Anthropic's guide to context engineering for AI agents using Claude.

83/100
7/7 frames
Top 34% of 14,551 measured
Legit Benchmark — the simple average of 7 measured frames. Frames we could not measure are left out of the average, never counted as zero. Every frame is shown below with its evidence.
Checked 2026-09-13 · scores move as sites change

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Legit.Show scored Effective context engineering for AI agents 83/100 on 2026-09-13, measured across all 7 frames from its public surface. legit.show/s/anthropic-com/2026-09-13

Is Effective context engineering for AI agents production-ready?

Legit.Show scores Effective context engineering for AI agents 83 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 Performance. Every frame it averages is published with its evidence on the Legit.Show listing.

The 7 Frames

What we measured

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

Sources and updates

Description
Taken from anthropic.com's own website on 2026-07-26.
Operator
Anthropic, PBC, as named in anthropic.com's terms, privacy page or footer.
Benchmark
Measured by Legit.Show from the live site, the way any visitor sees it — with no access to its code or accounts. Same method for every product, and no AI decides the score. Last checked 2026-09-13.

Put together from public information, without Effective context engineering for AI agents's involvement. If anything here is wrong, tell us and a person will check it.

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