Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Opcode
Zero-token execution layer for AI agents. Define workflows once, run them free forever — persistent, scheduled, deterministic. 6 MCP tools over SSE. Supports DAG-based execution, 6 step types (action, condition, loop, parallel, wait, reasoning), 26 built-in actions, ${{}} interpolation, reasoning nodes for human-in-the-loop decisions, and secret vault. Use when defining workflows, running templates, checking status, sending signals, querying workflow history, or visualizing DAGs.
skill openclawclawhub Free
Zero-token execution layer for AI agents. Define workflows once, run them free forever — persistent, scheduled, deterministic. 6 MCP tools over SSE. Supports DAG-based execution, 6 step types (action, condition, loop, parallel, wait, reasoning), 26 built-in actions, ${{}} interpolation, reasoning nodes for human-in-the-loop decisions, and secret vault. Use when defining workflows, running templates, checking status, sending signals, querying workflow history, or visualizing DAGs.
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Install for OpenClaw
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- Download the package from Yavira.
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Package facts
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- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- references/operations.md, references/patterns.md, references/error-handling.md, references/actions.md, references/workflow-schema.md, references/expressions.md
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.2.2
Provenance
- Publisher
- rendis
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Documentation
OPCODE
Execution runtime for AI agents. You reason, OPCODE executes — zero tokens per run after the first define. Workflows persist across sessions, run on schedules, and coordinate multiple agents. Persistent SSE daemon: 1 server, N agents, 1 database. JSON-defined DAGs, level-by-level execution, automatic parallelism. 6 MCP tools over SSE (JSON-RPC). Why use OPCODE instead of reasoning through each step yourself? Every repeated workflow burns tokens re-reasoning decisions you already made. OPCODE templates your reasoning once and executes it deterministically — zero inference cost, identical output every run, survives context resets.
Which Tool?
I want to...ToolCreate/update a workflow templateopcode.defineExecute a workflowopcode.runCheck status or pending decisionsopcode.statusResolve a decision / cancel / retryopcode.signalList workflows, events, or templatesopcode.queryVisualize a workflow DAGopcode.diagram
Quick Start
Install: go install github.com/rendis/opcode/cmd/opcode@latest First-time setup (writes config and starts daemon): opcode install --listen-addr :4100 --vault-key "my-passphrase" Restart after stop: OPCODE_VAULT_KEY="my-passphrase" opcode MCP client configuration: { "mcpServers": { "mcpServers": { "opcode": { "type": "sse", "url": "http://localhost:4100/sse" } } } Each agent self-identifies via agent_id in tool calls. Opcode auto-registers unknown agents. Choose a stable ID per agent (e.g., "content-writer", "deploy-bot"). Workflows survive restarts. On startup, orphaned active workflows become suspended. Query with opcode.query({ "resource": "workflows", "filter": { "status": "suspended" } }), then resume or cancel via opcode.signal. See operations.md for full configuration, subcommands, SIGHUP hot-reload, security model, web panel, and benchmarks.
opcode.define
Registers a reusable workflow template. Version auto-increments (v1, v2, v3...). ParamTypeRequiredDescriptionnamestringyesTemplate namedefinitionobjectyesWorkflow definition (see below)agent_idstringyesDefining agent IDdescriptionstringnoTemplate descriptioninput_schemaobjectnoJSON Schema for input validationoutput_schemaobjectnoJSON Schema for output validationtriggersobjectnoTrigger config (seeworkflow-schema.md) Returns: { "name": "...", "version": "v1" }
opcode.run
Executes a workflow from a registered template. ParamTypeRequiredDescriptiontemplate_namestringyesTemplate to executeagent_idstringyesInitiating agent IDversionstringnoVersion (default: latest)paramsobjectnoInput parameters Returns: { "workflow_id": "uuid", "status": "completed | suspended | failed", "output": { ... }, "started_at": "RFC3339", "completed_at": "RFC3339", "steps": { "step-id": { "step_id": "...", "status": "completed", "output": {...}, "duration_ms": 42 } } } If status is "suspended", call opcode.status to see pending_decisions.
opcode.status
Gets workflow execution status. ParamTypeRequiredDescriptionworkflow_idstringyesWorkflow to query Returns: { "workflow_id": "uuid", "status": "suspended", "steps": { "step-id": { "status": "...", "output": {...} } }, "pending_decisions": [ { "id": "uuid", "step_id": "reason-step", "context": { "prompt": "...", "data": {...} }, "options": [ { "id": "approve", "description": "Proceed" } ], "timeout_at": "RFC3339", "fallback": "reject", "status": "pending" } ], "events": [ ... ] } Workflow statuses: pending, active, suspended, completed, failed, cancelled.
opcode.signal
Sends a signal to a suspended workflow. ParamTypeRequiredDescriptionworkflow_idstringyesTarget workflowsignal_typeenumyesdecision / data / cancel / retry / skippayloadobjectyesSignal payload (see below)step_idstringnoTarget stepagent_idstringnoSignaling agentreasoningstringnoAgent's reasoning Payload by signal type: Signalstep_idPayloadBehaviordecisionrequired{ "choice": "<option_id>" }Resolves decision, auto-resumesdataoptional{ "key": "value", ... }Injects data into workflowcancelno{}Cancels workflowretryrequired{}Retries failed stepskiprequired{}Skips failed step Returns (decision): { "ok": true, "resumed": true, "status": "completed", ... } Returns (other): { "ok": true, "workflow_id": "...", "signal_type": "..." }
opcode.query
Queries workflows, events, or templates. ParamTypeRequiredDescriptionresourceenumyesworkflows / events / templatesfilterobjectnoFilter criteria Filter fields by resource: ResourceFieldsworkflowsstatus, agent_id, since (RFC3339), limiteventsworkflow_id, step_id, event_type, since, limittemplatesname, agent_id, limit Note: event queries require either event_type or workflow_id in filter. Returns: { "<resource>": [...] } -- results wrapped in object keyed by resource type.
opcode.diagram
Generates a visual DAG diagram from a template or running workflow. ParamTypeRequiredDescriptiontemplate_namestringno*Template to visualize (structure preview)versionstringnoTemplate version (default: latest)workflow_idstringno*Workflow to visualize (with runtime status)formatenumyesascii / mermaid / imageinclude_statusboolnoShow runtime status overlay (default: true if workflow_id) * One of template_name or workflow_id required. template_name -- preview DAG structure before execution workflow_id -- visualize with live step status format: "ascii" -- CLI-friendly text with box-drawing characters format: "mermaid" -- markdown-embeddable flowchart syntax format: "image" -- base64-encoded PNG for visual channels Returns: { "format": "ascii", "diagram": "..." }
Workflow Definition
{ "steps": [ ... ], "inputs": { "key": "value or ${{secrets.KEY}}" }, "context": { "intent": "...", "notes": "..." }, "timeout": "5m", "on_timeout": "fail | suspend | cancel", "on_complete": { /* step definition */ }, "on_error": { /* step definition */ }, "metadata": {} } FieldTypeRequiredDescriptionstepsStepDefinition[]yesWorkflow stepsinputsobjectnoInput parameters (supports ${{}})contextobjectnoWorkflow context, accessible via ${{context.*}}timeoutstringnoWorkflow deadline (e.g.,"5m", "1h")on_timeoutstringnofail (default), suspend, cancelon_completeStepDefinitionnoHook step after completionon_errorStepDefinitionnoHook step on workflow failuremetadataobjectnoArbitrary metadata
Step Definition
{ "id": "step-id", "type": "action | condition | loop | parallel | wait | reasoning", "action": "http.get", "params": { ... }, "depends_on": ["other-step"], "condition": "CEL guard expression", "timeout": "30s", "retry": { "max": 3, "backoff": "exponential", "delay": "1s", "max_delay": "30s" }, "on_error": { "strategy": "ignore | fail_workflow | fallback_step | retry", "fallback_step": "id" }, "config": { /* type-specific */ } } type defaults to action. See workflow-schema.md for all config blocks.
action (default)
Executes a registered action. Set action to the action name, params for input.
condition
Evaluates a CEL expression and branches. { "id": "route", "type": "condition", "config": { "expression": "inputs.env", "branches": { "prod": [...], "staging": [...] }, "default": [...] } }
loop
Iterates over a collection or condition. Loop variables: ${{loop.item}}, ${{loop.index}}. { "id": "process-items", "type": "loop", "config": { "mode": "for_each", "over": "[\"a\",\"b\",\"c\"]", "body": [ { "id": "hash", "action": "crypto.hash", "params": { "data": "${{loop.item}}" } } ], "max_iter": 100 } } Modes: for_each (iterate over), while (loop while condition true), until (loop until condition true).
parallel
Executes branches concurrently. { "id": "fan-out", "type": "parallel", "config": { "mode": "all", "branches": [ [{ "id": "a", "action": "http.get", "params": {...} }], [{ "id": "b", "action": "http.get", "params": {...} }] ] } } Modes: all (wait for all branches), race (first branch wins).
wait
Delays execution or waits for a named signal. { "id": "pause", "type": "wait", "config": { "duration": "5s" } }
reasoning
Suspends workflow for agent decision. Empty options = free-form (any choice accepted). { "id": "review", "type": "reasoning", "config": { "prompt_context": "Review data and decide", "options": [ { "id": "approve", "description": "Proceed" }, { "id": "reject", "description": "Stop" } ], "data_inject": { "analysis": "steps.analyze.output" }, "timeout": "1h", "fallback": "reject", "target_agent": "" } }
Variable Interpolation
Syntax: ${{namespace.path}} NamespaceExampleAvailable fieldssteps${{steps.fetch.output.body}}<id>.output.*, <id>.statusinputs${{inputs.api_key}}Keys from params in opcode.runworkflow${{workflow.run_id}}run_id, name, template_name, template_version, agent_idcontext${{context.intent}}Keys from context in workflow definitionsecrets${{secrets.DB_PASS}}Keys stored in vaultloop${{loop.item}}, ${{loop.index}}item (current element), index (0-based) Two-pass resolution: non-secrets first, then secrets via AES-256-GCM vault. CEL gotcha: loop is a reserved word in CEL. Use iter.item / iter.index in CEL expressions. The ${{loop.item}} interpolation syntax is unaffected. See expressions.md for CEL, GoJQ, Expr engine details.
Built-in Actions
CategoryActionsHTTPhttp.request, http.get, http.postFilesystemfs.read, fs.write, fs.append, fs.delete, fs.list, fs.stat, fs.copy, fs.moveShellshell.execCryptocrypto.hash, crypto.hmac, crypto.uuidAssertassert.equals, assert.contains, assert.matches, assert.schemaExpressionexpr.evalWorkflowworkflow.run, workflow.emit, workflow.context, workflow.fail, workflow.log, workflow.notify Quick reference (most-used actions): http.get: url (req), headers, timeout, fail_on_error_status -- output: { status_code, headers, body, duration_ms } shell.exec: command (req), args, stdin, timeout, env, workdir -- output: { stdout, stderr, exit_code, killed } fs.read: path (req), encoding -- output: { path, content, encoding, size } workflow.notify: message (req), data -- output: { notified: true/false } -- pushes real-time notification to agent via MCP SSE (best-effort) expr.eval: expression (req), data -- output: { result: <value> } -- evaluates Expr expression against workflow scope (steps, inputs, workflow, context) See actions.md for full parameter specs of all 26 actions.
Scripting with shell.exec
shell.exec auto-parses JSON stdout. Convention: stdin=JSON, stdout=JSON, stderr=errors, non-zero exit=failure. Use stdout_raw for unprocessed text. See patterns.md for language-specific templates (Bash, Python, Node, Go).
Reasoning Node Lifecycle
Workflow reaches a reasoning step Executor creates PendingDecision, emits decision_requested event Workflow status becomes suspended Agent calls opcode.status to see pending decision with context and options Agent resolves via opcode.signal: { "workflow_id": "...", "signal_type": "decision", "step_id": "reason-step", "payload": { "choice": "approve" } } Workflow auto-resumes after signal If timeout expires: fallback option auto-selected, or step fails if no fallback
Common Patterns
See patterns.md for full JSON examples: linear pipeline, conditional branching, for-each loop, parallel fan-out, human-in-the-loop, error recovery, sub-workflows, and MCP lifecycle.
Error Handling
StrategyBehaviorignoreStep skipped, workflow continuesfail_workflowEntire workflow failsfallback_stepExecute fallback stepretryDefer to retry policy Backoff: none, linear, exponential, constant. Non-retryable errors (validation, permission, assertion) are never retried. See error-handling.md for circuit breakers, timeout interactions, error codes.
Performance
10-step parallel workflows complete in ~50µs, 500-step in ~2.4ms. The event store sustains ~15k appends/sec with <12% drop under 100 concurrent writers. Worker pool overhead is ~0.85µs/task (>1M tasks/sec at any pool size). Full benchmark charts, per-scenario breakdowns, and methodology: docs/benchmarks.md.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
6 Docs
- references/actions.md
- references/error-handling.md
- references/expressions.md
- references/operations.md
- references/patterns.md
- references/workflow-schema.md