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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 (actio

v1.2.2
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Description


name: opcode description: > 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. license: MIT compatibility: > Requires Go 1.25+, CGO_ENABLED=1, and gcc or clang. Runs as SSE daemon on macOS and Linux. Linux: cgroups v2 for process isolation. macOS: timeout-only fallback. metadata: version: "1.2.1" transport: "sse" author: "rendis" repository: "https://github.com/rendis/opcode" primary-env: "OPCODE_VAULT_KEY" platforms: "darwin linux" requires-bins: "go gcc|clang" openclaw-emoji: "⚙️" openclaw-os: "darwin linux" openclaw-user-invocable: "true" openclaw-install-type: "go" openclaw-install-package: "github.com/rendis/opcode/cmd/opcode"

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... Tool
Create/update a workflow template opcode.define
Execute a workflow opcode.run
Check status or pending decisions opcode.status
Resolve a decision / cancel / retry opcode.signal
List workflows, events, or templates opcode.query
Visualize a workflow DAG opcode.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.

MCP Tools

opcode.define

Registers a reusable workflow template. Version auto-increments (v1, v2, v3...).

Param Type Required Description
name string yes Template name
definition object yes Workflow definition (see below)
agent_id string yes Defining agent ID
description string no Template description
input_schema object no JSON Schema for input validation
output_schema object no JSON Schema for output validation
triggers object no Trigger config (seeworkflow-schema.md)

Returns: { "name": "...", "version": "v1" }

opcode.run

Executes a workflow from a registered template.

Param Type Required Description
template_name string yes Template to execute
agent_id string yes Initiating agent ID
version string no Version (default: latest)
params object no Input 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.

Param Type Required Description
workflow_id string yes Workflow 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.

Param Type Required Description
workflow_id string yes Target workflow
signal_type enum yes decision / data / cancel / retry / skip
payload object yes Signal payload (see below)
step_id string no Target step
agent_id string no Signaling agent
reasoning string no Agent's reasoning

Payload by signal type:

Signal step_id Payload Behavior
decision required { "choice": "<option_id>" } Resolves decision, auto-resumes
data optional { "key": "value", ... } Injects data into workflow
cancel no {} Cancels workflow
retry required {} Retries failed step
skip required {} 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.

Param Type Required Description
resource enum yes workflows / events / templates
filter object no Filter criteria

Filter fields by resource:

Resource Fields
workflows status, agent_id, since (RFC3339), limit
events workflow_id, step_id, event_type, since, limit
templates name, 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.

Param Type Required Description
template_name string no* Template to visualize (structure preview)
version string no Template version (default: latest)
workflow_id string no* Workflow to visualize (with runtime status)
format enum yes ascii / mermaid / image
include_status bool no Show 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": {}
}
Field Type Required Description
steps StepDefinition[] yes Workflow steps
inputs object no Input parameters (supports ${{}})
context object no Workflow context, accessible via ${{context.*}}
timeout string no Workflow deadline (e.g.,"5m", "1h")
on_timeout string no fail (default), suspend, cancel
on_complete StepDefinition no Hook step after completion
on_error StepDefinition no Hook step on workflow failure
metadata object no Arbitrary 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.

Step Types

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}}

Namespace Example Available fields
steps ${{steps.fetch.output.body}} <id>.output.*, <id>.status
inputs ${{inputs.api_key}} Keys from params in opcode.run
workflow ${{workflow.run_id}} run_id, name, template_name, template_version, agent_id
context ${{context.intent}} Keys from context in workflow definition
secrets ${{secrets.DB_PASS}} Keys stored in vault
loop ${{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

Category Actions
HTTP http.request, http.get, http.post
Filesystem fs.read, fs.write, fs.append, fs.delete, fs.list, fs.stat, fs.copy, fs.move
Shell shell.exec
Crypto crypto.hash, crypto.hmac, crypto.uuid
Assert assert.equals, assert.contains, assert.matches, assert.schema
Expression expr.eval
Workflow workflow.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

  1. Workflow reaches a reasoning step

  2. Executor creates PendingDecision, emits decision_requested event

  3. Workflow status becomes suspended

  4. Agent calls opcode.status to see pending decision with context and options

  5. Agent resolves via opcode.signal:

    {
      "workflow_id": "...",
      "signal_type": "decision",
      "step_id": "reason-step",
      "payload": { "choice": "approve" }
    }
    
  6. Workflow auto-resumes after signal

  7. 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

Strategy Behavior
ignore Step skipped, workflow continues
fail_workflow Entire workflow fails
fallback_step Execute fallback step
retry Defer 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.

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Free

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