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Documentation Index

Fetch the complete documentation index at: https://jacobpevans-docs-automation-surface.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

The goal: file a GitHub Issue, grab coffee, come back to a PR that’s been implemented, tested, and reviewed by multiple AI models — just waiting for a thumbs up. Not fully there yet, but close enough to be dangerous. Humans decide what to build. AI agents handle the how. Automation runs the boring parts. A human gives the final sign-off. Claude, Gemini, Copilot, and local MLX models each do what they’re best at — the right model for the right job instead of throwing everything at one.

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The pipeline

Green nodes are human, coral are AI, ink are automation. The role is the node colour; the chain is the timeline — no zigzag because the diagram never asks the arrows to leave a column.

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The model-routing philosophy

Every model has a sweet spot:
  • Claude — best at multi-file refactors, deep reasoning, agentic loops. The default for non-trivial implementation work.
  • Gemini — great for second opinions, code review, broad context understanding.
  • GitHub Copilot — fastest for line-level completions inside the editor. Cheap for high-volume routine work.
  • Local MLX — Apple Silicon native inference for typo fixes, quick edits, and “I don’t want to burn cloud tokens on this” tasks.
The routing is opinionated, not magic: clear rules in ~/CLAUDE.md and AGENTS.md say which model to use when.

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Local AI gateway (Bifrost)

Bifrost is the OpenAI-compatible HTTP gateway that sits between every AI tool on the workstation and whichever provider eventually answers the call. It exposes http://localhost:30080/v1/chat/completions and fans out to OpenAI, Gemini, OpenRouter, and the local MLX server based on the task class.
  • Never hardcode model identifiers in committed config. Models change weekly; identifiers rot. Tools resolve task classes (Research, Coding, Review, Pre-commit) to a current model at call time via listmodels.
  • Local MLX models carry an mlx-local/ prefix when called through Bifrost (it expects provider/model format). Calling the vllm-mlx server directly on port 11434 uses the bare HuggingFace model ID — no prefix.
  • Cloud models go in unprefixed. Bifrost handles routing; do not add a provider prefix yourself.
When localOnlyMode is enabled (or the --local flag is passed), every task routes to the MLX inference server on port 11434 and no cloud API calls happen. Verify the LaunchAgent is running before invoking: launchctl list | grep vllm-mlx.

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PAL MCP

PAL MCP is the multi-model coordination layer on top of Bifrost. Two tools matter:
ToolPurpose
clinkMulti-model parallel calls — research and exploration
consensusMulti-model agreement — critical decisions
Every other PAL tool has a native Claude Code equivalent; for single-model calls, use Bifrost directly.

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Priority order

  1. Anthropic official — Claude Code plugins, skills, patterns
  2. Bifrost AI gateway — multi-provider routing at localhost:30080
  3. PAL MCP — only for clink and consensus
  4. Personal or custom — only when no alternative exists

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Repos that power this pipeline

ai-assistant-instructions

Universal AI configuration layer — rules, permissions, workflows, agents.

claude-code-plugins

Commands, skills, hooks, agents for Claude Code.

nix-ai

Nix package and config layer for every AI coding tool.

claude-code-routines

Scheduled remote-agent routines on Claude.ai.

ai-workflows

Reusable GitHub Copilot agentic workflows.

raycast-smart-issue

Raycast extension for AI-drafted GitHub issues via local MLX.
See AI Development · Overview for what each one does in detail. For the actual triggers, callers, and skill mechanics that drive this pipeline end-to-end, see Automation · Overview.

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Observability layer

Every interaction in this pipeline emits OpenTelemetry. The data flows through Cribl Edge, Cribl Stream, and Splunk; purpose-built Splunk apps visualize it. If an AI agent touched code, there’s a trace.