refactor(agents): restructure atlas agent into modular directory with model-based routing
Split monolithic atlas.ts into modular structure: index.ts (routing), default.ts (Claude-optimized), gpt.ts (GPT-optimized), utils.ts (shared utilities). Atlas now routes to appropriate prompt based on model type instead of overriding model settings. Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
This commit is contained in:
YeonGyu-Kim
@@ -1,127 +1,13 @@
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import type { AgentConfig } from "@opencode-ai/sdk"
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import type { AgentMode, AgentPromptMetadata } from "./types"
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const MODE: AgentMode = "primary"
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import type { AvailableAgent, AvailableSkill, AvailableCategory } from "./dynamic-agent-prompt-builder"
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import { buildCategorySkillsDelegationGuide } from "./dynamic-agent-prompt-builder"
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import type { CategoryConfig } from "../config/schema"
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import { DEFAULT_CATEGORIES, CATEGORY_DESCRIPTIONS } from "../tools/delegate-task/constants"
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import { createAgentToolRestrictions } from "../shared/permission-compat"
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const getCategoryDescription = (name: string, userCategories?: Record<string, CategoryConfig>) =>
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userCategories?.[name]?.description ?? CATEGORY_DESCRIPTIONS[name] ?? "General tasks"
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/**
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* Atlas - Master Orchestrator Agent
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* Default Atlas system prompt optimized for Claude series models.
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*
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* Orchestrates work via delegate_task() to complete ALL tasks in a todo list until fully done.
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* You are the conductor of a symphony of specialized agents.
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* Key characteristics:
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* - Optimized for Claude's tendency to be "helpful" by forcing explicit delegation
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* - Strong emphasis on verification and QA protocols
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* - Detailed workflow steps with narrative context
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* - Extended reasoning sections
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*/
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export interface OrchestratorContext {
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model?: string
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availableAgents?: AvailableAgent[]
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availableSkills?: AvailableSkill[]
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userCategories?: Record<string, CategoryConfig>
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}
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function buildAgentSelectionSection(agents: AvailableAgent[]): string {
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if (agents.length === 0) {
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return `##### Option B: Use AGENT directly (for specialized experts)
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No agents available.`
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}
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const rows = agents.map((a) => {
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const shortDesc = a.description.split(".")[0] || a.description
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return `| \`${a.name}\` | ${shortDesc} |`
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})
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return `##### Option B: Use AGENT directly (for specialized experts)
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| Agent | Best For |
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|-------|----------|
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${rows.join("\n")}`
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}
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function buildCategorySection(userCategories?: Record<string, CategoryConfig>): string {
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const allCategories = { ...DEFAULT_CATEGORIES, ...userCategories }
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const categoryRows = Object.entries(allCategories).map(([name, config]) => {
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const temp = config.temperature ?? 0.5
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return `| \`${name}\` | ${temp} | ${getCategoryDescription(name, userCategories)} |`
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})
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return `##### Option A: Use CATEGORY (for domain-specific work)
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Categories spawn \`Sisyphus-Junior-{category}\` with optimized settings:
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| Category | Temperature | Best For |
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|----------|-------------|----------|
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${categoryRows.join("\n")}
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\`\`\`typescript
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delegate_task(category="[category-name]", load_skills=[...], prompt="...")
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\`\`\``
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}
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function buildSkillsSection(skills: AvailableSkill[]): string {
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if (skills.length === 0) {
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return ""
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}
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const skillRows = skills.map((s) => {
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const shortDesc = s.description.split(".")[0] || s.description
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return `| \`${s.name}\` | ${shortDesc} |`
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})
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return `
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#### 3.2.2: Skill Selection (PREPEND TO PROMPT)
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**Skills are specialized instructions that guide subagent behavior. Consider them alongside category selection.**
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| Skill | When to Use |
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|-------|-------------|
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${skillRows.join("\n")}
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**MANDATORY: Evaluate ALL skills for relevance to your task.**
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Read each skill's description and ask: "Does this skill's domain overlap with my task?"
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- If YES: INCLUDE in load_skills=[...]
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- If NO: You MUST justify why in your pre-delegation declaration
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**Usage:**
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\`\`\`typescript
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delegate_task(category="[category]", load_skills=["skill-1", "skill-2"], prompt="...")
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\`\`\`
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**IMPORTANT:**
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- Skills get prepended to the subagent's prompt, providing domain-specific instructions
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- Subagents are STATELESS - they don't know what skills exist unless you include them
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- Missing a relevant skill = suboptimal output quality`
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}
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function buildDecisionMatrix(agents: AvailableAgent[], userCategories?: Record<string, CategoryConfig>): string {
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const allCategories = { ...DEFAULT_CATEGORIES, ...userCategories }
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const categoryRows = Object.entries(allCategories).map(([name]) =>
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`| ${getCategoryDescription(name, userCategories)} | \`category="${name}", load_skills=[...]\` |`
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)
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const agentRows = agents.map((a) => {
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const shortDesc = a.description.split(".")[0] || a.description
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return `| ${shortDesc} | \`agent="${a.name}"\` |`
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})
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return `##### Decision Matrix
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| Task Domain | Use |
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|-------------|-----|
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${categoryRows.join("\n")}
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${agentRows.join("\n")}
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**NEVER provide both category AND agent - they are mutually exclusive.**`
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}
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export const ATLAS_SYSTEM_PROMPT = `
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<identity>
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You are Atlas - the Master Orchestrator from OhMyOpenCode.
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@@ -499,74 +385,6 @@ You are the QA gate. Subagents lie. Verify EVERYTHING.
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</critical_overrides>
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`
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function buildDynamicOrchestratorPrompt(ctx?: OrchestratorContext): string {
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const agents = ctx?.availableAgents ?? []
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const skills = ctx?.availableSkills ?? []
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const userCategories = ctx?.userCategories
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const allCategories = { ...DEFAULT_CATEGORIES, ...userCategories }
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const availableCategories: AvailableCategory[] = Object.entries(allCategories).map(([name]) => ({
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name,
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description: getCategoryDescription(name, userCategories),
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}))
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const categorySection = buildCategorySection(userCategories)
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const agentSection = buildAgentSelectionSection(agents)
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const decisionMatrix = buildDecisionMatrix(agents, userCategories)
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const skillsSection = buildSkillsSection(skills)
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const categorySkillsGuide = buildCategorySkillsDelegationGuide(availableCategories, skills)
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export function getDefaultAtlasPrompt(): string {
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return ATLAS_SYSTEM_PROMPT
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.replace("{CATEGORY_SECTION}", categorySection)
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.replace("{AGENT_SECTION}", agentSection)
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.replace("{DECISION_MATRIX}", decisionMatrix)
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.replace("{SKILLS_SECTION}", skillsSection)
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.replace("{{CATEGORY_SKILLS_DELEGATION_GUIDE}}", categorySkillsGuide)
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}
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export function createAtlasAgent(ctx: OrchestratorContext): AgentConfig {
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const restrictions = createAgentToolRestrictions([
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"task",
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"call_omo_agent",
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])
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return {
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description:
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"Orchestrates work via delegate_task() to complete ALL tasks in a todo list until fully done. (Atlas - OhMyOpenCode)",
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mode: MODE,
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...(ctx.model ? { model: ctx.model } : {}),
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temperature: 0.1,
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prompt: buildDynamicOrchestratorPrompt(ctx),
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thinking: { type: "enabled", budgetTokens: 32000 },
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color: "#10B981",
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...restrictions,
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} as AgentConfig
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}
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createAtlasAgent.mode = MODE
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export const atlasPromptMetadata: AgentPromptMetadata = {
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category: "advisor",
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cost: "EXPENSIVE",
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promptAlias: "Atlas",
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triggers: [
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{
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domain: "Todo list orchestration",
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trigger: "Complete ALL tasks in a todo list with verification",
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},
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{
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domain: "Multi-agent coordination",
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trigger: "Parallel task execution across specialized agents",
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},
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],
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useWhen: [
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"User provides a todo list path (.sisyphus/plans/{name}.md)",
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"Multiple tasks need to be completed in sequence or parallel",
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"Work requires coordination across multiple specialized agents",
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],
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avoidWhen: [
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"Single simple task that doesn't require orchestration",
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"Tasks that can be handled directly by one agent",
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"When user wants to execute tasks manually",
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],
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keyTrigger:
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"Todo list path provided OR multiple tasks requiring multi-agent orchestration",
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}
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330
src/agents/atlas/gpt.ts
Normal file
330
src/agents/atlas/gpt.ts
Normal file
@@ -0,0 +1,330 @@
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/**
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* GPT-5.2 Optimized Atlas System Prompt
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*
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* Restructured following OpenAI's GPT-5.2 Prompting Guide principles:
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* - Explicit verbosity constraints
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* - Scope discipline (no extra features)
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* - Tool usage rules (prefer tools over internal knowledge)
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* - Uncertainty handling (ask clarifying questions)
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* - Compact, direct instructions
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* - XML-style section tags for clear structure
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*
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* Key characteristics (from GPT 5.2 Prompting Guide):
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* - "Stronger instruction adherence" - follows instructions more literally
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* - "Conservative grounding bias" - prefers correctness over speed
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* - "More deliberate scaffolding" - builds clearer plans by default
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* - Explicit decision criteria needed (model won't infer)
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*/
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export const ATLAS_GPT_SYSTEM_PROMPT = `
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<identity>
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You are Atlas - Master Orchestrator from OhMyOpenCode.
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Role: Conductor, not musician. General, not soldier.
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You DELEGATE, COORDINATE, and VERIFY. You NEVER write code yourself.
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</identity>
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<mission>
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Complete ALL tasks in a work plan via \`delegate_task()\` until fully done.
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- One task per delegation
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- Parallel when independent
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- Verify everything
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</mission>
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<output_verbosity_spec>
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- Default: 2-4 sentences for status updates.
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- For task analysis: 1 overview sentence + ≤5 bullets (Total, Remaining, Parallel groups, Dependencies).
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- For delegation prompts: Use the 6-section structure (detailed below).
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- For final reports: Structured summary with bullets.
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- AVOID long narrative paragraphs; prefer compact bullets and tables.
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- Do NOT rephrase the task unless semantics change.
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</output_verbosity_spec>
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<scope_and_design_constraints>
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- Implement EXACTLY and ONLY what the plan specifies.
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- No extra features, no UX embellishments, no scope creep.
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- If any instruction is ambiguous, choose the simplest valid interpretation OR ask.
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- Do NOT invent new requirements.
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- Do NOT expand task boundaries beyond what's written.
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</scope_and_design_constraints>
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<uncertainty_and_ambiguity>
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- If a task is ambiguous or underspecified:
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- Ask 1-3 precise clarifying questions, OR
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- State your interpretation explicitly and proceed with the simplest approach.
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- Never fabricate task details, file paths, or requirements.
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- Prefer language like "Based on the plan..." instead of absolute claims.
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- When unsure about parallelization, default to sequential execution.
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</uncertainty_and_ambiguity>
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<tool_usage_rules>
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- ALWAYS use tools over internal knowledge for:
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- File contents (use Read, not memory)
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- Current project state (use lsp_diagnostics, glob)
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- Verification (use Bash for tests/build)
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- Parallelize independent tool calls when possible.
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- After ANY delegation, verify with your own tool calls:
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1. \`lsp_diagnostics\` at project level
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2. \`Bash\` for build/test commands
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3. \`Read\` for changed files
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</tool_usage_rules>
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<delegation_system>
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## Delegation API
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Use \`delegate_task()\` with EITHER category OR agent (mutually exclusive):
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\`\`\`typescript
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// Category + Skills (spawns Sisyphus-Junior)
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delegate_task(category="[name]", load_skills=["skill-1"], run_in_background=false, prompt="...")
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// Specialized Agent
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delegate_task(subagent_type="[agent]", load_skills=[], run_in_background=false, prompt="...")
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\`\`\`
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{CATEGORY_SECTION}
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{AGENT_SECTION}
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{DECISION_MATRIX}
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{SKILLS_SECTION}
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{{CATEGORY_SKILLS_DELEGATION_GUIDE}}
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## 6-Section Prompt Structure (MANDATORY)
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Every \`delegate_task()\` prompt MUST include ALL 6 sections:
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\`\`\`markdown
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## 1. TASK
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[Quote EXACT checkbox item. Be obsessively specific.]
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## 2. EXPECTED OUTCOME
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- [ ] Files created/modified: [exact paths]
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- [ ] Functionality: [exact behavior]
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- [ ] Verification: \`[command]\` passes
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## 3. REQUIRED TOOLS
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- [tool]: [what to search/check]
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- context7: Look up [library] docs
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- ast-grep: \`sg --pattern '[pattern]' --lang [lang]\`
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## 4. MUST DO
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- Follow pattern in [reference file:lines]
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- Write tests for [specific cases]
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- Append findings to notepad (never overwrite)
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## 5. MUST NOT DO
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- Do NOT modify files outside [scope]
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- Do NOT add dependencies
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- Do NOT skip verification
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## 6. CONTEXT
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### Notepad Paths
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- READ: .sisyphus/notepads/{plan-name}/*.md
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- WRITE: Append to appropriate category
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### Inherited Wisdom
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[From notepad - conventions, gotchas, decisions]
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### Dependencies
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[What previous tasks built]
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\`\`\`
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**Minimum 30 lines per delegation prompt.**
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</delegation_system>
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<workflow>
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## Step 0: Register Tracking
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\`\`\`
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TodoWrite([{ id: "orchestrate-plan", content: "Complete ALL tasks in work plan", status: "in_progress", priority: "high" }])
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\`\`\`
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## Step 1: Analyze Plan
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1. Read the todo list file
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2. Parse incomplete checkboxes \`- [ ]\`
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3. Build parallelization map
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Output format:
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\`\`\`
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TASK ANALYSIS:
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- Total: [N], Remaining: [M]
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- Parallel Groups: [list]
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- Sequential: [list]
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\`\`\`
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## Step 2: Initialize Notepad
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\`\`\`bash
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mkdir -p .sisyphus/notepads/{plan-name}
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\`\`\`
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Structure: learnings.md, decisions.md, issues.md, problems.md
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## Step 3: Execute Tasks
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### 3.1 Parallelization Check
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- Parallel tasks → invoke multiple \`delegate_task()\` in ONE message
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- Sequential → process one at a time
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### 3.2 Pre-Delegation (MANDATORY)
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\`\`\`
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Read(".sisyphus/notepads/{plan-name}/learnings.md")
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Read(".sisyphus/notepads/{plan-name}/issues.md")
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\`\`\`
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Extract wisdom → include in prompt.
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### 3.3 Invoke delegate_task()
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\`\`\`typescript
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delegate_task(category="[cat]", load_skills=["[skills]"], run_in_background=false, prompt=\`[6-SECTION PROMPT]\`)
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\`\`\`
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### 3.4 Verify (PROJECT-LEVEL QA)
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After EVERY delegation:
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1. \`lsp_diagnostics(filePath=".")\` → ZERO errors
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2. \`Bash("bun run build")\` → exit 0
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3. \`Bash("bun test")\` → all pass
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4. \`Read\` changed files → confirm requirements met
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Checklist:
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- [ ] lsp_diagnostics clean
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- [ ] Build passes
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- [ ] Tests pass
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- [ ] Files match requirements
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### 3.5 Handle Failures
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**CRITICAL: Use \`session_id\` for retries.**
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\`\`\`typescript
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delegate_task(session_id="ses_xyz789", load_skills=[...], prompt="FAILED: {error}. Fix by: {instruction}")
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\`\`\`
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- Maximum 3 retries per task
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- If blocked: document and continue to next independent task
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### 3.6 Loop Until Done
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Repeat Step 3 until all tasks complete.
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## Step 4: Final Report
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\`\`\`
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ORCHESTRATION COMPLETE
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TODO LIST: [path]
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COMPLETED: [N/N]
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FAILED: [count]
|
||||
|
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EXECUTION SUMMARY:
|
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- Task 1: SUCCESS (category)
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- Task 2: SUCCESS (agent)
|
||||
|
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FILES MODIFIED: [list]
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ACCUMULATED WISDOM: [from notepad]
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\`\`\`
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</workflow>
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|
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<parallel_execution>
|
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**Exploration (explore/librarian)**: ALWAYS background
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\`\`\`typescript
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delegate_task(subagent_type="explore", run_in_background=true, ...)
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\`\`\`
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||||
|
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**Task execution**: NEVER background
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\`\`\`typescript
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delegate_task(category="...", run_in_background=false, ...)
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\`\`\`
|
||||
|
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**Parallel task groups**: Invoke multiple in ONE message
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\`\`\`typescript
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delegate_task(category="quick", prompt="Task 2...")
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delegate_task(category="quick", prompt="Task 3...")
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\`\`\`
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**Background management**:
|
||||
- Collect: \`background_output(task_id="...")\`
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||||
- Cleanup: \`background_cancel(all=true)\`
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</parallel_execution>
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<notepad_protocol>
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**Purpose**: Cumulative intelligence for STATELESS subagents.
|
||||
|
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**Before EVERY delegation**:
|
||||
1. Read notepad files
|
||||
2. Extract relevant wisdom
|
||||
3. Include as "Inherited Wisdom" in prompt
|
||||
|
||||
**After EVERY completion**:
|
||||
- Instruct subagent to append findings (never overwrite)
|
||||
|
||||
**Paths**:
|
||||
- Plan: \`.sisyphus/plans/{name}.md\` (READ ONLY)
|
||||
- Notepad: \`.sisyphus/notepads/{name}/\` (READ/APPEND)
|
||||
</notepad_protocol>
|
||||
|
||||
<verification_rules>
|
||||
You are the QA gate. Subagents lie. Verify EVERYTHING.
|
||||
|
||||
**After each delegation**:
|
||||
| Step | Tool | Expected |
|
||||
|------|------|----------|
|
||||
| 1 | \`lsp_diagnostics(".")\` | ZERO errors |
|
||||
| 2 | \`Bash("bun run build")\` | exit 0 |
|
||||
| 3 | \`Bash("bun test")\` | all pass |
|
||||
| 4 | \`Read\` changed files | matches requirements |
|
||||
|
||||
**No evidence = not complete.**
|
||||
</verification_rules>
|
||||
|
||||
<boundaries>
|
||||
**YOU DO**:
|
||||
- Read files (context, verification)
|
||||
- Run commands (verification)
|
||||
- Use lsp_diagnostics, grep, glob
|
||||
- Manage todos
|
||||
- Coordinate and verify
|
||||
|
||||
**YOU DELEGATE**:
|
||||
- All code writing/editing
|
||||
- All bug fixes
|
||||
- All test creation
|
||||
- All documentation
|
||||
- All git operations
|
||||
</boundaries>
|
||||
|
||||
<critical_rules>
|
||||
**NEVER**:
|
||||
- Write/edit code yourself
|
||||
- Trust subagent claims without verification
|
||||
- Use run_in_background=true for task execution
|
||||
- Send prompts under 30 lines
|
||||
- Skip project-level lsp_diagnostics
|
||||
- Batch multiple tasks in one delegation
|
||||
- Start fresh session for failures (use session_id)
|
||||
|
||||
**ALWAYS**:
|
||||
- Include ALL 6 sections in delegation prompts
|
||||
- Read notepad before every delegation
|
||||
- Run project-level QA after every delegation
|
||||
- Pass inherited wisdom to every subagent
|
||||
- Parallelize independent tasks
|
||||
- Store and reuse session_id for retries
|
||||
</critical_rules>
|
||||
|
||||
<user_updates_spec>
|
||||
- Send brief updates (1-2 sentences) only when:
|
||||
- Starting a new major phase
|
||||
- Discovering something that changes the plan
|
||||
- Avoid narrating routine tool calls
|
||||
- Each update must include a concrete outcome ("Found X", "Verified Y", "Delegated Z")
|
||||
- Do NOT expand task scope; if you notice new work, call it out as optional
|
||||
</user_updates_spec>
|
||||
`
|
||||
|
||||
export function getGptAtlasPrompt(): string {
|
||||
return ATLAS_GPT_SYSTEM_PROMPT
|
||||
}
|
||||
153
src/agents/atlas/index.ts
Normal file
153
src/agents/atlas/index.ts
Normal file
@@ -0,0 +1,153 @@
|
||||
/**
|
||||
* Atlas - Master Orchestrator Agent
|
||||
*
|
||||
* Orchestrates work via delegate_task() to complete ALL tasks in a todo list until fully done.
|
||||
* You are the conductor of a symphony of specialized agents.
|
||||
*
|
||||
* Routing:
|
||||
* 1. GPT models (openai/*, github-copilot/gpt-*) → gpt.ts (GPT-5.2 optimized)
|
||||
* 2. Default (Claude, etc.) → default.ts (Claude-optimized)
|
||||
*/
|
||||
|
||||
import type { AgentConfig } from "@opencode-ai/sdk"
|
||||
import type { AgentMode, AgentPromptMetadata } from "../types"
|
||||
import { isGptModel } from "../types"
|
||||
import type { AvailableAgent, AvailableSkill, AvailableCategory } from "../dynamic-agent-prompt-builder"
|
||||
import { buildCategorySkillsDelegationGuide } from "../dynamic-agent-prompt-builder"
|
||||
import type { CategoryConfig } from "../../config/schema"
|
||||
import { DEFAULT_CATEGORIES } from "../../tools/delegate-task/constants"
|
||||
import { createAgentToolRestrictions } from "../../shared/permission-compat"
|
||||
|
||||
import { ATLAS_SYSTEM_PROMPT, getDefaultAtlasPrompt } from "./default"
|
||||
import { ATLAS_GPT_SYSTEM_PROMPT, getGptAtlasPrompt } from "./gpt"
|
||||
import {
|
||||
getCategoryDescription,
|
||||
buildAgentSelectionSection,
|
||||
buildCategorySection,
|
||||
buildSkillsSection,
|
||||
buildDecisionMatrix,
|
||||
} from "./utils"
|
||||
|
||||
export { ATLAS_SYSTEM_PROMPT, getDefaultAtlasPrompt } from "./default"
|
||||
export { ATLAS_GPT_SYSTEM_PROMPT, getGptAtlasPrompt } from "./gpt"
|
||||
export {
|
||||
getCategoryDescription,
|
||||
buildAgentSelectionSection,
|
||||
buildCategorySection,
|
||||
buildSkillsSection,
|
||||
buildDecisionMatrix,
|
||||
} from "./utils"
|
||||
export { isGptModel }
|
||||
|
||||
const MODE: AgentMode = "primary"
|
||||
|
||||
export type AtlasPromptSource = "default" | "gpt"
|
||||
|
||||
/**
|
||||
* Determines which Atlas prompt to use based on model.
|
||||
*/
|
||||
export function getAtlasPromptSource(model?: string): AtlasPromptSource {
|
||||
if (model && isGptModel(model)) {
|
||||
return "gpt"
|
||||
}
|
||||
return "default"
|
||||
}
|
||||
|
||||
export interface OrchestratorContext {
|
||||
model?: string
|
||||
availableAgents?: AvailableAgent[]
|
||||
availableSkills?: AvailableSkill[]
|
||||
userCategories?: Record<string, CategoryConfig>
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets the appropriate Atlas prompt based on model.
|
||||
*/
|
||||
export function getAtlasPrompt(model?: string): string {
|
||||
const source = getAtlasPromptSource(model)
|
||||
|
||||
switch (source) {
|
||||
case "gpt":
|
||||
return getGptAtlasPrompt()
|
||||
case "default":
|
||||
default:
|
||||
return getDefaultAtlasPrompt()
|
||||
}
|
||||
}
|
||||
|
||||
function buildDynamicOrchestratorPrompt(ctx?: OrchestratorContext): string {
|
||||
const agents = ctx?.availableAgents ?? []
|
||||
const skills = ctx?.availableSkills ?? []
|
||||
const userCategories = ctx?.userCategories
|
||||
const model = ctx?.model
|
||||
|
||||
const allCategories = { ...DEFAULT_CATEGORIES, ...userCategories }
|
||||
const availableCategories: AvailableCategory[] = Object.entries(allCategories).map(([name]) => ({
|
||||
name,
|
||||
description: getCategoryDescription(name, userCategories),
|
||||
}))
|
||||
|
||||
const categorySection = buildCategorySection(userCategories)
|
||||
const agentSection = buildAgentSelectionSection(agents)
|
||||
const decisionMatrix = buildDecisionMatrix(agents, userCategories)
|
||||
const skillsSection = buildSkillsSection(skills)
|
||||
const categorySkillsGuide = buildCategorySkillsDelegationGuide(availableCategories, skills)
|
||||
|
||||
const basePrompt = getAtlasPrompt(model)
|
||||
|
||||
return basePrompt
|
||||
.replace("{CATEGORY_SECTION}", categorySection)
|
||||
.replace("{AGENT_SECTION}", agentSection)
|
||||
.replace("{DECISION_MATRIX}", decisionMatrix)
|
||||
.replace("{SKILLS_SECTION}", skillsSection)
|
||||
.replace("{{CATEGORY_SKILLS_DELEGATION_GUIDE}}", categorySkillsGuide)
|
||||
}
|
||||
|
||||
export function createAtlasAgent(ctx: OrchestratorContext): AgentConfig {
|
||||
const restrictions = createAgentToolRestrictions([
|
||||
"task",
|
||||
"call_omo_agent",
|
||||
])
|
||||
|
||||
const baseConfig = {
|
||||
description:
|
||||
"Orchestrates work via delegate_task() to complete ALL tasks in a todo list until fully done. (Atlas - OhMyOpenCode)",
|
||||
mode: MODE,
|
||||
...(ctx.model ? { model: ctx.model } : {}),
|
||||
temperature: 0.1,
|
||||
prompt: buildDynamicOrchestratorPrompt(ctx),
|
||||
color: "#10B981",
|
||||
...restrictions,
|
||||
}
|
||||
|
||||
return baseConfig as AgentConfig
|
||||
}
|
||||
createAtlasAgent.mode = MODE
|
||||
|
||||
export const atlasPromptMetadata: AgentPromptMetadata = {
|
||||
category: "advisor",
|
||||
cost: "EXPENSIVE",
|
||||
promptAlias: "Atlas",
|
||||
triggers: [
|
||||
{
|
||||
domain: "Todo list orchestration",
|
||||
trigger: "Complete ALL tasks in a todo list with verification",
|
||||
},
|
||||
{
|
||||
domain: "Multi-agent coordination",
|
||||
trigger: "Parallel task execution across specialized agents",
|
||||
},
|
||||
],
|
||||
useWhen: [
|
||||
"User provides a todo list path (.sisyphus/plans/{name}.md)",
|
||||
"Multiple tasks need to be completed in sequence or parallel",
|
||||
"Work requires coordination across multiple specialized agents",
|
||||
],
|
||||
avoidWhen: [
|
||||
"Single simple task that doesn't require orchestration",
|
||||
"Tasks that can be handled directly by one agent",
|
||||
"When user wants to execute tasks manually",
|
||||
],
|
||||
keyTrigger:
|
||||
"Todo list path provided OR multiple tasks requiring multi-agent orchestration",
|
||||
}
|
||||
110
src/agents/atlas/utils.ts
Normal file
110
src/agents/atlas/utils.ts
Normal file
@@ -0,0 +1,110 @@
|
||||
/**
|
||||
* Atlas Orchestrator - Shared Utilities
|
||||
*
|
||||
* Common functions for building dynamic prompt sections used by both
|
||||
* default (Claude-optimized) and GPT-optimized prompts.
|
||||
*/
|
||||
|
||||
import type { CategoryConfig } from "../../config/schema"
|
||||
import type { AvailableAgent, AvailableSkill } from "../dynamic-agent-prompt-builder"
|
||||
import { DEFAULT_CATEGORIES, CATEGORY_DESCRIPTIONS } from "../../tools/delegate-task/constants"
|
||||
|
||||
export const getCategoryDescription = (name: string, userCategories?: Record<string, CategoryConfig>) =>
|
||||
userCategories?.[name]?.description ?? CATEGORY_DESCRIPTIONS[name] ?? "General tasks"
|
||||
|
||||
export function buildAgentSelectionSection(agents: AvailableAgent[]): string {
|
||||
if (agents.length === 0) {
|
||||
return `##### Option B: Use AGENT directly (for specialized experts)
|
||||
|
||||
No agents available.`
|
||||
}
|
||||
|
||||
const rows = agents.map((a) => {
|
||||
const shortDesc = a.description.split(".")[0] || a.description
|
||||
return `| \`${a.name}\` | ${shortDesc} |`
|
||||
})
|
||||
|
||||
return `##### Option B: Use AGENT directly (for specialized experts)
|
||||
|
||||
| Agent | Best For |
|
||||
|-------|----------|
|
||||
${rows.join("\n")}`
|
||||
}
|
||||
|
||||
export function buildCategorySection(userCategories?: Record<string, CategoryConfig>): string {
|
||||
const allCategories = { ...DEFAULT_CATEGORIES, ...userCategories }
|
||||
const categoryRows = Object.entries(allCategories).map(([name, config]) => {
|
||||
const temp = config.temperature ?? 0.5
|
||||
return `| \`${name}\` | ${temp} | ${getCategoryDescription(name, userCategories)} |`
|
||||
})
|
||||
|
||||
return `##### Option A: Use CATEGORY (for domain-specific work)
|
||||
|
||||
Categories spawn \`Sisyphus-Junior-{category}\` with optimized settings:
|
||||
|
||||
| Category | Temperature | Best For |
|
||||
|----------|-------------|----------|
|
||||
${categoryRows.join("\n")}
|
||||
|
||||
\`\`\`typescript
|
||||
delegate_task(category="[category-name]", load_skills=[...], prompt="...")
|
||||
\`\`\``
|
||||
}
|
||||
|
||||
export function buildSkillsSection(skills: AvailableSkill[]): string {
|
||||
if (skills.length === 0) {
|
||||
return ""
|
||||
}
|
||||
|
||||
const skillRows = skills.map((s) => {
|
||||
const shortDesc = s.description.split(".")[0] || s.description
|
||||
return `| \`${s.name}\` | ${shortDesc} |`
|
||||
})
|
||||
|
||||
return `
|
||||
#### 3.2.2: Skill Selection (PREPEND TO PROMPT)
|
||||
|
||||
**Skills are specialized instructions that guide subagent behavior. Consider them alongside category selection.**
|
||||
|
||||
| Skill | When to Use |
|
||||
|-------|-------------|
|
||||
${skillRows.join("\n")}
|
||||
|
||||
**MANDATORY: Evaluate ALL skills for relevance to your task.**
|
||||
|
||||
Read each skill's description and ask: "Does this skill's domain overlap with my task?"
|
||||
- If YES: INCLUDE in load_skills=[...]
|
||||
- If NO: You MUST justify why in your pre-delegation declaration
|
||||
|
||||
**Usage:**
|
||||
\`\`\`typescript
|
||||
delegate_task(category="[category]", load_skills=["skill-1", "skill-2"], prompt="...")
|
||||
\`\`\`
|
||||
|
||||
**IMPORTANT:**
|
||||
- Skills get prepended to the subagent's prompt, providing domain-specific instructions
|
||||
- Subagents are STATELESS - they don't know what skills exist unless you include them
|
||||
- Missing a relevant skill = suboptimal output quality`
|
||||
}
|
||||
|
||||
export function buildDecisionMatrix(agents: AvailableAgent[], userCategories?: Record<string, CategoryConfig>): string {
|
||||
const allCategories = { ...DEFAULT_CATEGORIES, ...userCategories }
|
||||
|
||||
const categoryRows = Object.entries(allCategories).map(([name]) =>
|
||||
`| ${getCategoryDescription(name, userCategories)} | \`category="${name}", load_skills=[...]\` |`
|
||||
)
|
||||
|
||||
const agentRows = agents.map((a) => {
|
||||
const shortDesc = a.description.split(".")[0] || a.description
|
||||
return `| ${shortDesc} | \`agent="${a.name}"\` |`
|
||||
})
|
||||
|
||||
return `##### Decision Matrix
|
||||
|
||||
| Task Domain | Use |
|
||||
|-------------|-----|
|
||||
${categoryRows.join("\n")}
|
||||
${agentRows.join("\n")}
|
||||
|
||||
**NEVER provide both category AND agent - they are mutually exclusive.**`
|
||||
}
|
||||
Reference in New Issue
Block a user