The routing decision is about reasoning capacity, not cost or provider.
Fast model (koala/qwen35-9b-fast) handles high-pass-rate calls; thinking
model (iguana/gemma4-26b) handles low-pass-rate calls. Removes the
implicit Anthropic dependency from the routing pod — both models go
through LiteLLM.
Renames: HYPERGUILD_LOCAL_MODEL → HYPERGUILD_FAST_MODEL,
HYPERGUILD_CLAUDE_MODEL → HYPERGUILD_THINKING_MODEL,
Router.LocalModel → FastModel, Router.ClaudeModel → ThinkingModel,
log decision "claude_fallback" → "thinking_fallback".
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Typed config struct and env parser for the routing pod. Kept separate
from the supervisor Config to avoid forcing routing fields onto the
supervisor and vice versa. Uses the existing envOr helper from config.go.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Enables exposing the supervisor MCP via Tailscale Funnel for claude.ai
custom-connector tests. Auth is opt-in: empty SUPERVISOR_MCP_TOKEN
preserves the existing unauthenticated behavior for tailnet-internal
callers and local dev.
When the token is set, every request must carry
"Authorization: Bearer <token>" or it is rejected with HTTP 401 and a
JSON-RPC -32001 error. Comparison uses crypto/subtle.ConstantTimeCompare;
the token value and the supplied header are never logged.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Drop the three-layer Claude subprocess orchestration (local model →
Claude verifier → cloud escalation). Skills now call LiteLLM directly
and return plain text to Claude Code, which decides what to do with it.
- Delete executor, orchestrator, verifier, result, attempts packages
- Simplify LiteLLMExecutor: Run(Request)→Result becomes Complete(model,sys,user)→(string,int64,error)
- Replace ExecutorFn with CompleteFunc in all 6 skill configs
- Rewrite all skill handlers to call Complete and return {"text","model","duration_ms"}
- Simplify config/models: remove Verifier/LlamaSwapURL, add ModelFor
- Bump version to v0.5.0
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements escalation chains per skill with three-layer priority:
1. Caller override (model param) — no escalation
2. Per-skill chain from models.yaml
3. default_chain fallback
New APIs:
- Verifier() — fixed verifier for output validation
- LlamaSwapURL() — base URL for warm-state probing
- ChainFor(skill, override) — ordered model list for escalation
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
