Provides AI coding agents with structured, evidence-based diagnostics about the local development environment, detecting tech stack, runtime mismatches, dependency state, services, ports, and Git status without exposing secrets or using network calls.
Enables coding agents to query, compare, and audit local profiler traces, benchmarks, memory captures, and execution evidence without uploading code or data, using CLI and MCP interfaces.
Offers proof-only tools to inspect and verify remediation closure receipts, deterministically confirming asset coverage, fixed artifact deployment, rescanning, deadline compliance, and zero-residual closure without executing scans or touching live systems.
A local-first, model-neutral MCP server for collecting and normalizing change-scoped release evidence. It provides deterministic Git change summaries, evidence collection, and review bundles for agent review.
Enables AI agents to query persistent, build-scoped evidence memory for reverse engineering, combining static analysis, runtime captures, and claims with honest uncertainty. Provides read-only access to an evidence graph and MCP prompts for structured investigations.
Enables LLM agents to safely reclaim disk space by deleting build artifact directories like node_modules, .venv, and target, with strong guardrails to prevent accidental or malicious deletion.
