Enables acceptance gates for AI coding-agent runs by recording evidence, running deterministic validation, applying a quality gate, and rendering auditable outcomes.
Enables traceable requirement discovery, technical alignment, and ISO-aligned process checking through deterministic MCP tools and resources, without requiring an embedded LLM.
Enables defining and verifying evidence contracts for claims in READMEs, releases, or product pages using constrained verifiers and generating hash-chained receipts and reports.
Implements GitHub's Spec-Driven Development methodology, transforming natural language requirements into executable specifications, technical plans, and ordered task lists with contract-based validation and progress tracking.
Enables AI coding agents to record auditable work ledgers with evidence chains, from contract to proof packet, via MCP tools for file scanning, code review, and issue triage.