ce45592730
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>
50 lines
1.2 KiB
Go
50 lines
1.2 KiB
Go
// internal/skills/retrospective/skill.go
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package retrospective
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import (
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"context"
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"encoding/json"
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"github.com/mathiasbq/supervisor/internal/registry"
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)
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// CompleteFunc is the function used to call a local model.
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type CompleteFunc func(ctx context.Context, model, system, user string) (string, int64, error)
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// Config holds retrospective skill configuration.
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type Config struct {
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SkillPrompt string
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DefaultModel string
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SessionsDir string
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CompleteFunc CompleteFunc
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}
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// Skill implements registry.Skill for the retrospective tool.
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type Skill struct {
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cfg Config
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}
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// New constructs a retrospective Skill.
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func New(cfg Config) *Skill { return &Skill{cfg: cfg} }
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// Name returns the skill name.
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func (s *Skill) Name() string { return "retrospective" }
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// Tools returns the MCP tool definitions.
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func (s *Skill) Tools() []registry.ToolDef {
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return []registry.ToolDef{
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{
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Name: "retrospective",
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Description: "Consult a local model to analyse a completed session and identify what is novel or worth preserving as organizational knowledge.",
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InputSchema: json.RawMessage(`{
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"type": "object",
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"required": ["session_id"],
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"properties": {
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"session_id": {"type": "string"},
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"model": {"type": "string"}
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}
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}`),
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},
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}
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}
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