#Context

A3S Code treats context as a budgeted resource. The model should see the smallest useful context for the current decision, not every available file, skill, memory, and tool log.

#Sources

Context can come from:

• user prompt and conversation history
• AGENTS.md project instructions
• skills and agent definitions
• memory stores
• file search and direct tool results
• MCP tools and context providers
• delegated task summaries
• trace events

AGENTS.md injection, skills discovery, memory APIs, direct tool results, delegated task helpers, and traceEvents() are part of the documented Node SDK surface. Validate MCP context behavior against your own live integrations before documenting it as product behavior.

#Assembly

sources -> ContextItem -> rank -> dedupe -> budget -> render

Long grep output, logs, and child transcripts should be preserved outside the prompt and summarized into prompt-safe evidence. Use session.traceEvents() for compact runtime evidence.

#Exact Cognitive Packages (Rust Host)

An embedding Rust host can bind a session to one exact A3S Use cognitive-package generation. A3S Code does not install packages, resolve a Registry entry, or select latest; the host injects both an immutable CognitivePackageBindingV1 and a provider holding the matching Knowledge lease.

use a3s_code_core::{CognitiveContextSession, SessionOptions};

let cognitive_context = CognitiveContextSession::new(binding, provider)?;
let options = SessionOptions::new().with_cognitive_context(cognitive_context);

The durable a3s.code.cognitive-package-session-binding.v1 identity includes the package id/version, lifecycle generation, generation digest, capability snapshot digest, exact Knowledge surface, and prompt-injection limits. Each typed request and cited Markdown response repeats that binding and is validated before content enters model context.

The hard limits are four documents, 6 KiB per document, and 6 KiB total. The host may choose smaller limits in the binding. Provider failure, malformed citations, request mismatch, or generation drift fails closed instead of falling back to unrelated retrieval.

Use with_cognitive_context; adding a cognitive provider through the generic context-provider list is rejected because its binding could not be persisted correctly. An exact cognitive package cannot accompany general-purpose RAG or graph providers, and personal-memory recall is suppressed. Code-owned workspace instructions and skills remain available.

The binding is stored in the session snapshot and emitted as cognitive_context_bound. On resume, the host must re-inject a provider with the same binding; a missing or different generation is rejected. This typed boundary is currently a Rust-host integration surface rather than a Node.js, Python, or Go session option.

#Compaction

Enable automatic compaction for long sessions:

const session = agent.session('/repo', {
  autoCompact: true,
  autoCompactThreshold: 0.75,
  maxContextTokens: 128_000,
});

When maxContextTokens is omitted, Core uses the selected model's declared context window when available. Before each model request, Core accounts for the system prompt, conversation, tool calls and results, and exposed tool schemas. At the configured threshold it bounds oversized tool output, summarizes the older safe prefix, keeps recent messages, and continues the same task. The summary participates in later compactions, so long sessions can roll forward through repeated compression; this does not enlarge the model's physical single-request context window. A successful context_compacted event includes the cumulative summary so hosts that supply external history can persist the same compact generation across turns.

Python exposes the same override as max_context_tokens.