Contexta Key Features
Contexta is a single product surface for local-first ML observability workflows.
Instead of treating capture, storage, query, comparison, reporting, and recovery as separate tools, Contexta brings them under one canonical product identity:
- Python import root:
contexta - CLI target:
contexta - env prefix:
CONTEXTA_* - workspace root:
.contexta/
What Is Contexta?
Contexta is designed for teams that want to:
- keep observability data local and inspectable
- use canonical models instead of ad-hoc payloads
- query and compare runs from the same product surface that wrote them
- keep recovery inside the product instead of as external scripts
The intended core loop is:
- capture
- store
- query
- report
Everything else in the product is organized around making that loop reliable and inspectable.
The Main Product Outcomes
One Product Instead Of Six Separate Surfaces
Contexta replaces the idea of many independent primary surfaces with one canonical surface.
What this gives you:
- one public product identity
- one public import root
- one public workspace shape
- one place to look first when starting new code
Local-First By Default
The product is built around a local workspace and local inspection.
This means:
- you can create and inspect data without a remote service
- canonical data lives in a workspace you control
- query and reporting do not require a hosted platform to make sense
Embedded HTTP/UI may exist as delivery surfaces, but they are still local-first and local-only by design.
Canonical Data Instead Of Ad-Hoc Logs
Contexta is organized around canonical models for:
- context
- records
- artifacts
- lineage and provenance
This matters because:
- query results are more stable
- reports can be built from a predictable schema
- degraded or incomplete states can be expressed explicitly instead of being hidden in free-form text
Unified Read And Investigation Flow
Once canonical data exists in the workspace, Contexta can read it through one investigation surface.
That includes:
- run listing
- run snapshots
- comparison
- diagnostics
- lineage traversal
- report generation
The point is not only to store data, but to make it inspectable in a consistent way.
Recovery Is Part Of The Product
Contexta treats recovery as a first-class concern rather than an afterthought.
That includes:
- replay
- backup
- restore
This matters because observability systems become hard to trust when recovery depends on custom scripts and undocumented operator knowledge.
Feature Map
| Feature Area | What It Gives You |
|---|---|
| Unified facade | A single starting point for the product |
| Local workspace | Inspectable, local-first canonical storage |
| Canonical contract | Stable models, validation, and serialization |
| Investigation layer | Query, compare, diagnostics, lineage, reports |
| Recovery layer | Replay, backup, restore |
Who Benefits Most
New Users
New users benefit from:
- one place to start
- one naming system to learn
- a clear path from quickstart to deeper usage
Operators
Operators benefit from:
- explicit workspace ownership
- recovery in the same product story
- a clearer boundary between public surface and internal implementation
What This Section Does Not Promise
This section describes the product direction and stable public shape. It does not claim that every release-alignment detail is already complete.
In the current prototype stage:
- canonical naming is already
Contexta/contexta - some packaging and CLI alignment work is still in progress
- the public docs set is still being filled out
Use this section as the conceptual overview, then continue with: