Docs

Start with the public docs

• Getting Started gives evaluators and design partners a narrow first-metric path for proving the context layer against real workflows.
• Features Overview maps the public ClariLayer app journey from Metric Studio authoring to registry discovery, warehouse validation, release governance, trust monitoring, and API context delivery.
• Integrations and Admin explains the public boundary for warehouses, dbt export, identity, GitHub and Jira handoff, approval notifications, API keys, service accounts, and enterprise controls.
• The Context Layer explains how Metric Lifecycle Management turns metric meaning, variants, validation, and reasoning into AI-ready context.
• The Reasoning Trail explains how ClariLayer captures the human conversation behind a metric definition: decisions, unresolved objections, clarifications, and curated notes for AI context.
• API v1 Overview explains the public read-only API surface for metric discovery, metric detail, and agent-facing contracts.
• API v1 Authentication explains API keys, Agent Contract scopes, legacy compatibility, sandbox headers, rate limits, and revocation.
• Metrics List and Detail documents list, search, filtering, pagination, and detail response shapes.
• GET /api/v1/metrics/{id}/contract documents the agent-facing contract envelope, including request shape, scope requirements, discussion fields, summary behavior, and degradation semantics.
• AI Agent Context Guide shows how to ground agents with lifecycle state, pinned notes, managed variants, and traceable contract context.

Choose your path

ClariLayer's public docs give evaluators, product learners, integration builders, API consumers, and AI-agent builders a direct route through the same metric lifecycle.

• Evaluators: start with Getting Started. It shows how to pick one meaningful metric, capture the business definition, validate it against the warehouse, review the release path, and make the same governed context available to humans and AI agents.

• Product learners: read Features Overview, then The Context Layer and The Reasoning Trail. Those pages explain how ClariLayer turns metric meaning, approval evidence, release history, caveats, and discussion into context that can be trusted after the original meeting or review is over.

• Integration builders: read Integrations and Admin, then API v1 Authentication. Those pages explain the public boundary for warehouses, dbt export, identity, GitHub and Jira handoff, approval notifications, API keys, service accounts, and enterprise controls.

• API consumers: start with API v1 Overview, Metrics List and Detail, and the metrics contract endpoint. The API reference covers read-only metric discovery, detail responses, scope requirements, sandbox headers, rate limits, and the contract envelope an external workflow can request for a single metric.

• AI-agent builders: use the AI Agent Context Guide after you understand the contract API. It focuses on lifecycle status, validation evidence, pinned Reasoning Trail notes, managed variants, traceability, and cache refresh behavior so an agent can avoid guessing which metric definition is canonical.

Current public docs map

Overview

Start with the evaluator path when you need a practical proof around one high-value metric.

Features

The feature docs explain the public product journey at the product and API level. Start with the overview when you need the app flow before you go deeper into Metric Studio, registry discovery, validation, governance, trust signals, or the API.

Concepts

The concept docs explain the mental model behind ClariLayer's metric context layer. Start with the context layer when you need the broad architecture, then read the Reasoning Trail when you need to understand how human discussion becomes agent-readable context.

API Reference

The API reference docs describe public v1 read contracts. Start with authentication, then metrics list/detail, then the metrics contract page when an AI agent, BI integration, or workflow automation needs the canonical context for one governed metric.

Guides

The guide docs show how to consume the public API safely. The first guide focuses on AI-agent context: discovery, contract fetches, lifecycle handling, pinned notes, managed variants, and cache refresh.