Skill UI

This skill provides a deterministic, git-only method to verify claims made by AI agents (e.g., 'done', 'shipped', 'fixed'). Instead of trusting the agent's self-report, it audits the commit's diff and git history using the DOS kernel (`dos verify`, `dos commit-audit`) to confirm if the claimed change genuinely occurred and is backed by non-forgeable evidence. It acts as a critical quality gate.

This skill designs and audits the core engineering harness required for reliable AI agent collaboration within a codebase. It establishes critical infrastructure elements such as change tracking, linting rules, CI/CD gates, and standardized documentation, ensuring the repository remains the single source of truth for all intelligent agents. Ideal for setting up complex development workflows.

This skill guides coding agents through a comprehensive memory loop using AccInt's MCP server. It allows agents to retrieve prior outcomes, resolve complex reasoning frames, and formally close commitments with verifiable evidence (e.g., passing tests, successful merges). Essential for managing non-trivial, multi-step development workflows and ensuring work builds on genuine results.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.

This skill enables the creation of a robust 'harness' system for coding agents within a repository. It addresses the need to prevent repeated AI-generated coding mistakes by implementing durable instructions, guardrails, regression tests, and failure memory. It treats the target repository as the source of truth, ensuring consistency and maintaining high reliability across all automated contributions.

This skill acts as a central router, helping users determine the correct specialized skill or workflow to tackle development challenges. It guides the entire software development lifecycle, from initial idea refinement (Idea -> Ship) and prototype testing, to managing complex multi-session builds and handling incoming bugs via triage. It is essential for navigating the vast ecosystem of AI coding agents.