Context Engineering
Context engineering is the practice of curating the information that large language models receive at inference time so that the model can perform a task reliably and cost-effectively. It treats the context window as a finite attention budget and looks for the smallest set of high-signal tokens that maximize the likelihood of the desired outcome. Context engineering subsumes and extends prompt engineering, system prompts, tool design, retrieval, agent loops, structured note taking, compaction, and multi-agent decomposition. It is a foundational discipline for building production AI agents and assistants.
Context Engineering is tracked in the API Evangelist network. This page is the human-readable profile that sits on top of the machine-readable index we maintain at apis.io.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Context Engineering is in the network as a tracked entity. We haven't yet indexed a public API surface for it — when one is published, the artifacts, score, and agent-readiness read will appear here automatically. The source repository is where that profile is built.
← All providers · Data indexed from github.com/api-evangelist/context-engineering · machine-readable index on apis.io
This is an independent, third-party profile of Context Engineering, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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