# Send Cord Trees to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "cord-trees", "name": "Cord Trees", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/MoltonBot000/cord-trees", "canonicalUrl": "https://clawhub.ai/MoltonBot000/cord-trees", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/cord-trees", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=cord-trees", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "references/state-helpers.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "cord-trees", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T20:54:53.210Z", "expiresAt": "2026-05-07T20:54:53.210Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=cord-trees", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=cord-trees", "contentDisposition": "attachment; filename=\"cord-trees-1.0.1.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "cord-trees" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/cord-trees" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "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/cord-trees", "downloadUrl": "https://openagent3.xyz/downloads/cord-trees", "agentUrl": "https://openagent3.xyz/skills/cord-trees/agent", "manifestUrl": "https://openagent3.xyz/skills/cord-trees/agent.json", "briefUrl": "https://openagent3.xyz/skills/cord-trees/agent.md" } } ``` ## Documentation ### Cord Trees — Dynamic Task Tree Orchestration Build coordination trees at runtime. You decide the decomposition, not the developer. Inspired by Cord by June Kim. ### Core Concept Instead of following a pre-defined workflow, you analyze the goal and build your own task tree: Goal: "Evaluate whether to migrate from REST to GraphQL" You decide: ├── #1 spawn: Audit current REST API surface ├── #2 spawn: Research GraphQL trade-offs ├── #3 ask: How many concurrent users? (blocked-by: #1) ├── #4 fork: Comparative analysis (blocked-by: #2, #3) └── #5 fork: Write recommendation (blocked-by: #4) The tree emerges from your analysis, not from hardcoded logic. ### 1. SPAWN — Isolated Context Child gets only its task prompt. Clean slate. spawn( goal="Research GraphQL adoption patterns", prompt="Search for case studies of REST→GraphQL migrations...", blocked_by=[] # Can start immediately ) Use when: Task is self-contained, doesn't need sibling context. ### 2. FORK — Inherited Context Child receives all completed sibling results injected into prompt. fork( goal="Synthesize findings into recommendation", prompt="Based on the research, write a recommendation...", blocked_by=["research-rest", "research-graphql", "user-scale"] ) Use when: Synthesis, analysis, or integration requiring prior work. ### 3. ASK — Human Elicitation Pause for human input. Creates a checkpoint. ask( question="How many concurrent users do you serve?", options=["<1K", "1K-10K", "10K-100K", ">100K"], blocked_by=["audit-api"] # Ask after audit provides context ) Use when: Decision requires human knowledge or approval. ### 4. SERIAL — Ordered Sequence Children execute in order. Implicit dependencies. serial([ {"goal": "Draft report", "type": "spawn"}, {"goal": "Review draft", "type": "ask"}, {"goal": "Finalize report", "type": "fork"} ]) Use when: Strict ordering required. ### 5. GOAL — Root Node The top-level objective. You decompose it into children. ### Implementation with OpenClaw Map Cord primitives to OpenClaw tools: Cord PrimitiveOpenClaw Implementationspawnsessions_spawn(task=prompt, label=id)forksessions_spawn with sibling results in taskaskMessage human, wait for responseserialSpawn sequentially, wait between eachread_treeRead state file + subagents listcompleteWrite result to state file ### State File Track the tree in cord-state.json: { "goal": "Evaluate REST to GraphQL migration", "nodes": { "#1": { "type": "spawn", "goal": "Audit REST API", "status": "complete", "result": "47 endpoints, 12 nested...", "blockedBy": [], "sessionKey": "abc123" }, "#2": { "type": "spawn", "goal": "Research GraphQL", "status": "running", "blockedBy": [], "sessionKey": "def456" }, "#3": { "type": "ask", "goal": "Get user scale", "status": "waiting", "question": "How many concurrent users?", "options": ["<1K", "1K-10K", "10K-100K", ">100K"], "blockedBy": ["#1"] }, "#4": { "type": "fork", "goal": "Comparative analysis", "status": "blocked", "blockedBy": ["#2", "#3"] } }, "nextId": 5 } ### Phase 1: Analyze Goal Read the goal. Think about: What are the major components? What can run in parallel? What has dependencies? Where do I need human input? What needs synthesis (fork) vs isolation (spawn)? ### Phase 2: Build Initial Tree Create nodes for the first level of decomposition: # Initialize state state = { "goal": user_goal, "nodes": {}, "nextId": 1 } # Add initial nodes add_node(state, type="spawn", goal="Research A", blockedBy=[]) add_node(state, type="spawn", goal="Research B", blockedBy=[]) add_node(state, type="fork", goal="Synthesize", blockedBy=["#1", "#2"]) write("cord-state.json", state) ### Phase 3: Execute Ready Nodes Find nodes that are ready (all blockedBy complete): def get_ready_nodes(state): ready = [] for id, node in state["nodes"].items(): if node["status"] != "blocked": continue deps = node["blockedBy"] if all(state["nodes"][d]["status"] == "complete" for d in deps): ready.append(id) return ready For each ready node: If spawn: sessions_spawn( task=node["prompt"], label=node_id, runTimeoutSeconds=600 ) node["status"] = "running" If fork: # Inject sibling results sibling_context = collect_sibling_results(state, node) full_prompt = f"{node['prompt']}\\n\\nContext from prior work:\\n{sibling_context}" sessions_spawn(task=full_prompt, label=node_id) node["status"] = "running" If ask: # Message human message(action="send", message=f"Question: {node['question']}\\nOptions: {node['options']}") node["status"] = "waiting" # Wait for response, then mark complete with answer ### Phase 4: Monitor & Update Poll running agents, update state on completion: while has_running_or_blocked(state): # Check agent status agents = subagents(action="list") for agent in agents: node = find_node_by_session(state, agent["sessionKey"]) if agent["status"] == "complete": # Get result from session history result = get_agent_result(agent) node["status"] = "complete" node["result"] = result # Dispatch newly ready nodes for node_id in get_ready_nodes(state): dispatch_node(state, node_id) save_state(state) wait(30) # Don't poll too aggressively ### Phase 5: Synthesize When all nodes complete, the final fork node produces the result. ### Dynamic Restructuring Agents can modify their own subtree at runtime: # Child agent realizes it needs more research add_child_node( parent="#2", type="spawn", goal="Deep dive on performance implications", blockedBy=[] ) This is what makes Cord-style orchestration powerful — the tree evolves based on what agents discover. ### Spawn vs Fork Decision Guide SituationUseIndependent research taskspawnTask that doesn't need sibling contextspawnCheap to restart if it failsspawnSynthesis or analysis across prior workforkFinal integration stepforkTask that builds on discoveriesfork Default to spawn. Use fork only when context inheritance is required. ### Approval Gate #1 spawn: Draft proposal #2 ask: "Approve this proposal?" (blocked-by: #1) #3 fork: Implement approved proposal (blocked-by: #2) ### Clarification #1 spawn: Initial analysis #2 ask: "Which direction should we focus?" (blocked-by: #1) #3 spawn: Deep dive on chosen direction (blocked-by: #2) ### Periodic Checkpoints #1 spawn: Phase 1 #2 ask: "Continue to phase 2?" (blocked-by: #1) #3 spawn: Phase 2 (blocked-by: #2) #4 ask: "Continue to phase 3?" (blocked-by: #3) ... ### Example: Full Decomposition Goal: "Create a comprehensive competitor analysis report" #1 [spawn] List top 5 competitors └── No dependencies, starts immediately #2 [spawn] Research Competitor A (blocked-by: #1) #3 [spawn] Research Competitor B (blocked-by: #1) #4 [spawn] Research Competitor C (blocked-by: #1) #5 [spawn] Research Competitor D (blocked-by: #1) #6 [spawn] Research Competitor E (blocked-by: #1) └── All parallel, isolated research #7 [fork] Identify patterns across competitors (blocked-by: #2-#6) └── Needs all research results #8 [ask] "Focus on pricing, features, or positioning?" (blocked-by: #7) └── Human steers direction #9 [fork] Deep analysis on chosen focus (blocked-by: #8) └── Builds on patterns + human input #10 [fork] Write final report (blocked-by: #9) └── Synthesis of everything ### Error Handling if node["status"] == "failed": # Options: # 1. Retry (reset to blocked) node["status"] = "blocked" node["retries"] = node.get("retries", 0) + 1 # 2. Skip (mark complete with error) node["status"] = "complete" node["result"] = f"FAILED: {error}" # 3. Escalate (ask human) add_node(state, type="ask", question=f"Node {id} failed. Retry, skip, or abort?", blockedBy=[]) ### Attribution This skill implements patterns from the Cord protocol by June Kim, adapted for OpenClaw's sessions_spawn and subagents primitives. ## Trust - Source: tencent - Verification: Indexed source record - Publisher: MoltonBot000 - Version: 1.0.1 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-04-30T20:54:53.210Z - Expires at: 2026-05-07T20:54:53.210Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/cord-trees) - [Send to Agent page](https://openagent3.xyz/skills/cord-trees/agent) - [JSON manifest](https://openagent3.xyz/skills/cord-trees/agent.json) - [Markdown brief](https://openagent3.xyz/skills/cord-trees/agent.md) - [Download page](https://openagent3.xyz/downloads/cord-trees)