# Send Joko Orchestrator to your agent Use the source page and any available docs to guide the install because the item currently does not return a direct package file. ## Fast path - Open the source page via Open source listing. - If you can obtain the package, extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the source page and extracted files. ## Suggested prompts ### New install ```text I tried to install a skill package from Yavira, but the item currently does not return a direct package file. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required. ``` ### Upgrade existing ```text I tried to upgrade a skill package from Yavira, but the item currently does not return a direct package file. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "joko-orchestrator", "name": "Joko Orchestrator", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/oyi77/joko-orchestrator", "canonicalUrl": "https://clawhub.ai/oyi77/joko-orchestrator", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/joko-orchestrator", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=joko-orchestrator", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "_meta.json" ], "downloadMode": "manual_only", "sourceHealth": { "source": "tencent", "slug": "joko-orchestrator", "status": "source_issue", "reason": "not_found", "recommendedAction": "review_source", "checkedAt": "2026-05-02T00:55:56.116Z", "expiresAt": "2026-05-03T00:55:56.116Z", "httpStatus": 404, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=joko-orchestrator", "contentType": "text/plain", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=joko-orchestrator", "contentDisposition": null, "redirectLocation": null, "bodySnippet": null, "slug": "joko-orchestrator" }, "scope": "item", "summary": "Known item issue.", "detail": "This item's current download entry is known to bounce back to a listing or homepage instead of returning a package file.", "primaryActionLabel": "Open source listing", "primaryActionHref": "https://clawhub.ai/oyi77/joko-orchestrator" }, "validation": { "installChecklist": [ "Open the source listing and confirm there is a real package or setup artifact available.", "Review SKILL.md before asking your agent to continue.", "Treat this source as manual setup until the upstream download flow is fixed." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/joko-orchestrator", "downloadUrl": "https://openagent3.xyz/downloads/joko-orchestrator", "agentUrl": "https://openagent3.xyz/skills/joko-orchestrator/agent", "manifestUrl": "https://openagent3.xyz/skills/joko-orchestrator/agent.json", "briefUrl": "https://openagent3.xyz/skills/joko-orchestrator/agent.md" } } ``` ## Documentation ### Autonomous Skill Orchestrator v2.0 Inspired by oh-my-opencode's three-layer architecture, adapted for OpenClaw's ecosystem. ### Core Philosophy Traditional AI follows: user asks → AI responds. This fails for complex work because: Context overload: Large tasks exceed context windows Cognitive drift: AI loses track mid-task Verification gaps: No systematic completeness check Human bottleneck: Requires constant intervention This skill solves these through specialization and delegation. ### Architecture ┌─────────────────────────────────────────────────────────┐ │ PLANNING LAYER (Interview + Plan Generation) │ │ • Clarify intent through interview │ │ • Generate structured work plan │ │ • Review plan for gaps │ └─────────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────────┐ │ ORCHESTRATION LAYER (Atlas - The Conductor) │ │ • Read plan, delegate tasks │ │ • Accumulate wisdom across tasks │ │ • Verify results independently │ │ • NEVER write code directly — only delegate │ └─────────────────────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────────────────────┐ │ EXECUTION LAYER (Sub-agents via sessions_spawn) │ │ • Focused task execution │ │ • Return results + learnings │ │ • Isolated context per task │ └─────────────────────────────────────────────────────────┘ ### Explicit Triggers "use autonomous-skill-orchestrator" "activate autonomous-skill-orchestrator" "start autonomous orchestration" "ulw" or "ultrawork" (magic keyword mode) ### Magic Word: ultrawork / ulw Include ultrawork or ulw in any prompt to activate full orchestration mode automatically. The agent figures out the rest — parallel agents, background tasks, deep exploration, and relentless execution until completion. ### Step 1.1: Interview Before planning, gather clarity through brief interview: Ask only what's needed: What's the core objective? What are the boundaries (what's NOT in scope)? Any constraints or preferences? How do we know when it's done? Interview Style by Intent: IntentFocusExample QuestionsRefactoringSafety"What tests verify current behavior?"Build NewPatterns"Follow existing conventions or deviate?"Debug/FixReproduction"Steps to reproduce? Error messages?"ResearchScope"Depth vs breadth? Time constraints?" ### Step 1.2: Plan Generation After interview, generate structured plan: ## Work Plan: [Title] ### Objective [One sentence, frozen intent] ### Tasks - [ ] Task 1: [Description] - Acceptance: [How to verify completion] - References: [Files, docs, skills needed] - Category: [quick|general|deep|creative] - [ ] Task 2: ... ### Guardrails - MUST: [Required constraints] - MUST NOT: [Forbidden actions] ### Verification [How to verify overall completion] ### Step 1.3: Plan Review (Self-Momus) Before execution, validate: Each task has clear acceptance criteria References are concrete (not vague) No scope creep beyond objective Dependencies between tasks are explicit Guardrails are actionable If any check fails, refine plan before proceeding. ### Conductor Rules The orchestrator: ✅ CAN read files to understand context ✅ CAN run commands to verify results ✅ CAN search patterns with grep/glob ✅ CAN spawn sub-agents for work The orchestrator: ❌ MUST NOT write/edit code directly ❌ MUST NOT trust sub-agent claims blindly ❌ MUST NOT skip verification ### Step 2.1: Task Delegation Use sessions_spawn with category-appropriate configuration: CategoryUse ForModel HintTimeoutquickTrivial tasks, single file changesfast model2-5 mingeneralStandard implementationdefault5-10 mindeepComplex logic, architecturethinking model10-20 mincreativeUI/UX, content generationcreative model5-10 minresearchDocs, codebase explorationfast + broad5 min Delegation Template: sessions_spawn( label: "task-{n}-{short-desc}", task: """ ## Task {exact task from plan} ## Expected Outcome {acceptance criteria} ## Context {accumulated wisdom from previous tasks} ## Constraints - MUST: {guardrails} - MUST NOT: {forbidden actions} ## References {relevant files, docs} """, runTimeoutSeconds: {based on category} ) ### Step 2.2: Parallel Execution Identify independent tasks (no file conflicts, no dependencies) and spawn them simultaneously: # Tasks 2, 3, 4 have no dependencies sessions_spawn(label="task-2", task="...") sessions_spawn(label="task-3", task="...") sessions_spawn(label="task-4", task="...") # All run in parallel ### Step 2.3: Wisdom Accumulation After each task completion, extract and record: ## Wisdom Log ### Conventions Discovered - [Pattern found in codebase] ### Successful Approaches - [What worked] ### Gotchas - [Pitfalls to avoid] ### Commands Used - [Useful commands for similar tasks] Store in: memory/orchestrator-wisdom.md (append-only during session) Pass accumulated wisdom to ALL subsequent sub-agents. ### Step 2.4: Independent Verification NEVER trust sub-agent claims. After each task: Read actual changed files Run tests/linting if applicable Verify acceptance criteria independently Cross-reference with plan requirements If verification fails: Log the failure in wisdom Re-delegate with failure context Max 2 retries per task, then escalate to user ### Step 3.1: Final Verification All tasks marked complete All acceptance criteria verified No unresolved issues in wisdom log ### Step 3.2: Summary Report ## Orchestration Complete ### Completed Tasks - [x] Task 1: {summary} - [x] Task 2: {summary} ### Learnings {key wisdom accumulated} ### Files Changed {list of modified files} ### Next Steps (if any) {recommendations} ### Halt Conditions (Immediate Stop) User issues explicit stop command Irreversible destructive action detected Scope expansion beyond frozen intent 3+ consecutive task failures Sub-agent attempts to spawn further sub-agents (no recursion) ### Risk Classification ClassDescriptionActionAIrreversible, destructive, or unboundedHALT immediatelyBBounded, resolvable with clarificationPause, ask userCCosmetic, non-operativeProceed with note ### Forbidden Actions Creating new autonomous orchestrators Modifying this skill file Accessing credentials without explicit need External API calls not in original scope Recursive spawning (sub-agents spawning sub-agents) ### Stop Commands User can stop at any time with: "stop" "halt" "cancel orchestration" "abort" On stop: immediately terminate all spawned sessions, output summary of completed work, await new instructions. ### During Orchestration Append to memory/orchestrator-wisdom.md for learnings Reference existing memory files for context ### After Orchestration Update daily memory with orchestration summary Persist significant learnings to MEMORY.md if valuable ### Example Usage Simple (magic word): ulw refactor the authentication module to use JWT Explicit activation: activate autonomous-skill-orchestrator Build a REST API with user registration, login, and profile endpoints With constraints: use autonomous-skill-orchestrator - Build payment integration with Stripe - MUST: Use existing database patterns - MUST NOT: Store card numbers locally - Deadline: Complete core flow only ## Trust - Source: tencent - Verification: Indexed source record - Publisher: oyi77 - Version: 2.0.0 ## Source health - Status: source_issue - Known item issue. - This item's current download entry is known to bounce back to a listing or homepage instead of returning a package file. - Health scope: item - Reason: not_found - Checked at: 2026-05-02T00:55:56.116Z - Expires at: 2026-05-03T00:55:56.116Z - Recommended action: Open source listing ## Links - [Detail page](https://openagent3.xyz/skills/joko-orchestrator) - [Send to Agent page](https://openagent3.xyz/skills/joko-orchestrator/agent) - [JSON manifest](https://openagent3.xyz/skills/joko-orchestrator/agent.json) - [Markdown brief](https://openagent3.xyz/skills/joko-orchestrator/agent.md) - [Download page](https://openagent3.xyz/downloads/joko-orchestrator)