Agent context layer
A context layer for AI coding agents
AI coding agents should not depend on whichever prompt, model, or developer happened to explain the codebase last. Schemyx gives teams a stable context layer that agents can query before they make changes.
The problem
Prompt memory is not team memory.
Teams lose consistency when product knowledge lives in chat history, scattered docs, and one-off project summaries. The next agent run may not know the last decision, even when the codebase already has a pattern.
Schemyx approach
Schemyx separates durable context from the prompt.
Schemyx scans the codebase, extracts reusable facts, and serves them as stable recipes. Agents can retrieve the same standards on every task, while teams can review collisions and approve canonical patterns.
Why teams use it
Less drift, faster onboarding, and the same context across agents.
Outcome
Designed for multi-agent workflows
When several agents work across the same product, they need one source of truth for components, routes, API rules, and data constraints. Schemyx keeps that source outside any single chat.
Outcome
Automatic updates after code changes
As the codebase changes, Schemyx can regenerate the context layer so the next lookup reflects current files instead of old onboarding docs.
Outcome
Review when patterns collide
If the scanner finds several button systems, route styles, or model conventions, the bundle can flag review items instead of pretending every pattern is canonical.
Lookup examples
The useful detail lives behind stable keys.
Schemyx is built for exact reads. Agents can ask for a concept, resolve a key, then fetch a tiny context response before they write.
cluster.ui.button
Canonical UI patterns
Find competing button, card, badge, input, and nav patterns before agents copy the wrong one.
cluster.theme.tokens
Theme source of truth
Resolve color, spacing, radius, and typography tokens before generated UI drifts.
service.EmailDeliveryService
Service behavior
Expose service responsibilities, dependencies, and side effects to the agent.
model.SalesCallSignup
Data continuity
Keep generated admin screens and API handlers aligned with the same database shape.
Workflow
From codebase scan to agent-safe generation.
Schemyx keeps the heavy context work out of the prompt and turns repeated decisions into reusable lookup responses.
01
Extract the facts
Scan local source and capture facts as file, component, route, API, service, model, style, and rule recipes.
02
Resolve concepts
Search terms and aliases map natural requests to stable keys instead of forcing agents to guess file paths.
03
Fetch a context pack
The agent receives the target recipe plus direct dependencies and review warnings.
04
Fall back safely
If context is incomplete, the recipe points to the source file so the agent can read only what is needed.
Who it is for
Built for teams and builders who want AI work to stay coherent.
Audience
Teams using several AI tools
Keep Codex, Cursor, Claude, and local agents aligned on the same source of truth.
Audience
Product engineers
Stop repeating product rules and implementation details before every generated change.
Audience
Technical leaders
Give new hires and agents a visual map of how the product actually works.
FAQ
Questions teams ask before trusting agent context.
Is this only for frontend projects?
No. Schemyx is designed to capture frontend, backend, API, database, docs, tests, config, and style context.
Can the context layer work across frameworks?
Yes. Schemyx uses a generic recipe model with framework-specific extractors where deeper parsing is useful.
What makes it different from documentation?
Documentation is usually written for humans. Schemyx creates small, structured lookup responses built for agents to use while writing code.
Does the team control what becomes canonical?
Yes. Review items can expose duplicates, collisions, and uncertain patterns so teams can decide what agents should reuse.
Next step
Give every agent the same source of truth.
Request beta access or book a call to map Schemyx against your current stack, team standards, and agent workflow.