Stop your AI from making things up — it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is the proving ground. MCP server + CLI.

Pasal.id - The first open, AI-native Indonesian legal platform. MCP server + REST API + web app giving AI grounded access Indonesian laws.

Vendor-neutral OpenTelemetry skills for AI coding agents, grounded in upstream sources

Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents

Agent Skills that turn novels into source-grounded, fully playable games for Claude Code, Codex, and Kimi Code(K3).

Local-first AI coding personality profiler, usage dashboard, and evidence-grounded roast.

Anti-hallucination research mode for Claude Code. Toggle on/off to enforce citation requirements and source grounding.

Grounded Docs MCP Server: Open-Source Alternative to Context7, Nia, and Ref.Tools

Agent-driven proactive memory CLI for AI agents — autonomously recall, maintain, and evolve persistent, source-grounded knowledge across sessions.

Project continuity for Claude Code and Codex: a roadmap beside your code, grounded handoffs, and clear task status.

Teach your AI to draw correct, beautiful draw.io diagrams — declarative layout engine, ground-truth stencils, structural validator, vision self-check. AWS · Azure · GCP · Databricks · BPMN. Zero dependencies.

Kubernetes Skill for Claude Code and Codex. LLMs hallucinate a lot with K8s - KubeShark fixes this. It eliminates hallucinations and grounds your Kubernetes, Helm etc official best practices.

Architecture-first skill lifecycle for AI agents. BinEval binary scoring with threshold-blind, cross-family-calibrated judges, gated self-update loop, pressure testing, 10 authoring principles grounded in empirical research.

Local-first static analysis that turns source code into deterministic, source-grounded workflow maps for coding agents via MCP.

Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.

AI code reviews grounded in 12 classic engineering books — decay risk diagnostics with book citations, severity labels, and 6 analysis modes including full-sweep auto-fix

Team memory for engineers and their AI agents. Lives in your repo. Shared through Git.