type: workstream slug: context-catalog-nimble name: context catalog nimble description: Context catalog architecture and Nimble integration into product workflows. owner: data-ai-engineer-architect status: active milestones: m0-prototype: |- A runnable prototype path exists for context schema/catalog contracts and Nimble enrichment flows across product surfaces, with concrete artifacts that prove the flow works end-to-end in the current codebase. Core assumptions are documented, known constraints are explicit, and the team can explain what is real versus mocked without ambiguity. m1-ft-analytics-analyst-pilot: |- Internal analysts can execute at least one weekly real workflow that depends on context schema/catalog contracts and Nimble enrichment flows across product surfaces in the 5T Analytics environment, without bespoke engineering intervention for every run. Instrumentation and feedback capture are in place so failures, friction points, and adoption gaps are visible and triaged with owners. m2-internal-adoption-design-partners: |- context schema/catalog contracts and Nimble enrichment flows across product surfaces is hardened enough for regular use by multiple internal teams and initial design partners, with a predictable response loop for issues and requests. Quality expectations are documented, and prioritized improvements from real usage are actively incorporated into delivery. m3-public-launch: |- Launch scope for context schema/catalog contracts and Nimble enrichment flows across product surfaces is complete, externally explainable, and supportable: user-facing behavior is stable, documentation is publishable, and operational ownership is explicit. Remaining gaps are non-blocking, risk-assessed, and tracked as post-launch follow-up rather than unresolved launch debt. m4-v1-0-launch: |- Post-launch stabilization is complete for context schema/catalog contracts and Nimble enrichment flows across product surfaces: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements. m5-v1-2-launch: |- v1.2 delivers meaningful depth improvements in context schema/catalog contracts and Nimble enrichment flows across product surfaces based on observed usage and retention signals, not just roadmap intent. Enhancements improve real customer outcomes, and release readiness is demonstrated through metrics, regression coverage, and clear migration guidance where relevant. mx-far-future-ideas: |- Long-horizon opportunities for context schema/catalog contracts and Nimble enrichment flows across product surfaces are captured as concrete hypotheses with user impact, prerequisites, and evaluation criteria. Ideas are ranked by strategic value and feasibility so future investment decisions can be made quickly with less rediscovery.
Context architecture/catalog and Nimble integration into inspect, MCP, and generation flows. This workstream defines how data context is structured, stored, and surfaced across the product — the "catalog" of what we know about a user's data and how it's made available to humans and AI. Nimble is the methodology for lightweight dbt model linting and context enrichment. This workstream owns the context schema, the Nimble rule engine, and the integration points where context flows into inspect (profiler output), MCP (agent tools), and dashboard generation (smarter defaults). Adjacent to inspect-profiler (which produces raw context) and mcp-analyst-agent (which consumes context for AI workflows).
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