memex-cli

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Execute AI-powered command-line tasks with memory, replay, and resume capabilities using memex-cli. Use when (1) Running AI backend tasks (codex, claude, gemini), (2) Replaying recorded events from JSONL files, (3) Resuming interrupted runs by run_id, (4) Executing prompts with streaming output in jsonl or text format.

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When & Why to Use This Skill

The memex-cli skill is a robust command-line interface designed for orchestrating complex AI workflows across multiple backends, including Claude, Gemini, and Codex. It enables developers to execute AI-powered tasks with advanced memory management, allowing for the resumption of interrupted runs and the replaying of recorded events. By supporting both parallel execution and Directed Acyclic Graph (DAG) task dependencies, it provides a professional-grade environment for structured AI task automation, context-aware file loading, and seamless integration into existing CI/CD or development pipelines.

Use Cases

  • Complex Task Orchestration: Define and execute multiple AI tasks in parallel or as a sequential DAG (Directed Acyclic Graph) to handle multi-step engineering workflows.
  • Iterative Development with Resume: Use the unique Run ID and resume capability to continue long-running AI generations or add features to previous implementations without losing context.
  • Multi-Backend AI Integration: Switch between Codex for code generation, Claude for architectural design, and Gemini for multimodal UI/UX analysis within a single unified CLI protocol.
  • Automated AI Benchmarking and Replay: Replay recorded AI interactions from JSONL files to evaluate model consistency or debug specific task failures in a reproducible environment.
  • Context-Aware Code Refactoring: Load local project files using glob patterns and 'embed' or 'ref' modes to provide AI models with the necessary codebase context for accurate refactoring.
namememex-cli
description"Execute AI tasks (codex/claude/gemini) with memory and resume support via memex-cli stdin protocol."

Memex CLI

A CLI wrapper for AI backends (Codex, Claude, Gemini) with built-in memory and resume capabilities.

Core Concepts

memex-cli uses stdin protocol to define tasks, allowing:

  • Multi-backend AI execution (codex, claude, gemini)
  • Parallel and sequential task orchestration
  • Resume from previous runs with full context
  • File loading for context-aware tasks
  • Structured output (text or JSONL)

Basic Task Syntax

memex-cli run --stdin <<'EOF'
---TASK---
id: <task_id>
backend: <backend>
workdir: <working_directory>
---CONTENT---
<prompt>
---END---
EOF

Required Parameters

Parameter Description Example
id Unique task identifier implement-auth-20260110
backend AI backend codex, claude, gemini
workdir Working directory path ./project or /home/user/app
<prompt> Task prompt content Describe what to implement

Optional Parameters

Parameter Description Default Example
model Specific model name Backend default gpt-5.2, gpt-5.1-codex-max
model-provider Model provider openai For codex backend
dependencies Task dependencies None task-a or task-a,task-b
timeout Timeout in seconds 300 600 (10 minutes)
retry Retry count on failure 0 2 (retry twice)
files File paths to load None src/**/*.py (glob supported)
files-mode File handling mode embed ref, auto
files-encoding File encoding utf-8 base64, auto
stream-format Output format text jsonl

Backend Selection

Codex - Code Generation

Optimized for code implementation and refactoring.

---TASK---
id: code-gen
backend: codex
workdir: ./project
model: gpt-5.2
---CONTENT---
实现用户认证模块
---END---

Best for: Code generation, refactoring, test writing

Claude - Design & Architecture

Optimized for system design and architecture planning.

---TASK---
id: design
backend: claude
workdir: ./project
---CONTENT---
设计 REST API 架构
---END---

Best for: System design, architecture, documentation

Gemini - Multimodal Tasks

Supports image and document analysis.

---TASK---
id: ux-review
backend: gemini
workdir: ./project
files: ./mockups/*.png
files-mode: embed
---CONTENT---
审查 UX 设计稿
---END---

Best for: UI/UX review, image analysis, multimodal tasks

Task ID Patterns

Recommended patterns:

# Timestamp format (unique)
task-20260110143052
implement-auth-20260110143052

# Semantic format (readable)
design-api
implement-backend
test-integration

# Hierarchical format (organized)
auth.design
auth.implement
auth.test

Avoid generic IDs like task1, task2.

Multi-Task Execution

Define multiple tasks in one stdin input:

memex-cli run --stdin <<'EOF'
---TASK---
id: task-1
backend: codex
workdir: ./project
---CONTENT---
First task
---END---

---TASK---
id: task-2
backend: codex
workdir: ./project
---CONTENT---
Second task
---END---
EOF

Execution modes:

  • Parallel (default) - Tasks without dependencies run simultaneously
  • DAG (sequential) - Tasks with dependencies: run in order

See references/advanced-usage.md for detailed multi-task documentation.

Resume Functionality

Continue from a previous run using --run-id:

# Initial run outputs Run ID
memex-cli run --stdin < task.md
# Output: Run ID: abc123-def456

# Resume from that run
memex-cli resume --run-id abc123-def456 --stdin <<'EOF'
---TASK---
id: continue
backend: codex
workdir: ./project
---CONTENT---
基于之前的实现添加功能
---END---
EOF

Context preservation:

  • Previous task outputs available
  • Conversation history maintained
  • File changes visible

See references/advanced-usage.md for resume strategies.

Output Formats

Text Format (Default)

Human-readable with status markers:

▶ task-id (backend/model)
[AI output content]
» 写入 file.py
✓ task-id 3.5s

Status markers: ▶ (start), ✓ (success), ✗ (failed), ⟳ (retry), » (action)

JSONL Format

Machine-readable JSON Lines for programmatic parsing:

memex-cli run --stdin --stream-format jsonl < tasks.md

Output:

{"v":1,"type":"task.start","ts":"2026-01-10T10:00:00Z","run_id":"abc","task_id":"code-gen"}
{"v":1,"type":"assistant.output","ts":"2026-01-10T10:00:01Z",...}
{"v":1,"type":"task.end","ts":"2026-01-10T10:00:03Z",...}

See references/output-formats.md for complete format specifications.

Quick Start Examples

Single task:

memex-cli run --stdin < examples/basic-task.md

Parallel tasks:

memex-cli run --stdin < examples/parallel-tasks.md

DAG workflow:

memex-cli run --stdin < examples/dag-workflow.md

All examples are in examples/ directory with full task definitions.

Additional Resources

Reference Documentation

For detailed information on advanced features:

  • references/output-formats.md - Complete output format specifications

    • Text format status markers
    • JSONL event types
    • Parsing examples
  • references/advanced-usage.md - Advanced usage patterns

    • Multi-task parallel execution
    • DAG dependency configuration
    • Resume strategies
    • File loading modes
    • Timeout and retry configuration
  • references/troubleshooting.md - Comprehensive troubleshooting guide

    • Installation and authentication issues
    • Task execution failures
    • File loading problems
    • Dependency and resume errors
    • Performance optimization
    • Advanced debugging techniques

Working Examples

Ready-to-use task files in examples/:

  • examples/basic-task.md - Single task implementation
  • examples/parallel-tasks.md - Independent parallel tasks
  • examples/dag-workflow.md - Complete workflow with dependencies
  • examples/resume-workflow.md - Iterative development with resume

Copy and customize these examples for your projects.

Common Workflows

Code Implementation

# Generate code with Codex
memex-cli run --stdin <<'EOF'
---TASK---
id: implement-feature
backend: codex
workdir: ./project
model: gpt-5.2
---CONTENT---
实现用户认证模块
---END---
EOF

Design Phase

# Design with Claude
memex-cli run --stdin <<'EOF'
---TASK---
id: design-system
backend: claude
workdir: ./project
---CONTENT---
设计系统架构
---END---
EOF

UX Review

# Review mockups with Gemini
memex-cli run --stdin <<'EOF'
---TASK---
id: review-ui
backend: gemini
workdir: ./project
files: mockups/*.png
files-mode: embed
---CONTENT---
审查 UI 设计稿
---END---
EOF

Iterative Development

# 1. Initial implementation
RUN_ID=$(memex-cli run --stdin < task.md | grep "Run ID:" | awk '{print $3}')

# 2. Add features
memex-cli resume --run-id $RUN_ID --stdin < add-features.md

# 3. Fix bugs
memex-cli resume --run-id $RUN_ID --stdin < bugfixes.md

Best Practices

Task ID naming:

  • Use descriptive, semantic names
  • Include timestamps for uniqueness
  • Hierarchical naming for organization

Backend selection:

  • Codex → Code generation
  • Claude → Design, architecture
  • Gemini → Multimodal, UI/UX

Dependency management:

  • Keep DAG shallow (2-3 levels)
  • Parallelize independent tasks
  • Use resume for long workflows

File loading:

  • Small files (<50 KB) → files-mode: embed
  • Large files (>50 KB) → files-mode: ref
  • Mixed sizes → files-mode: auto

Output format:

  • Interactive use → text (default)
  • Automation → jsonl for parsing

Troubleshooting

Common issues:

  • "memex-cli command not found" → Install: npm install -g memex-cli
  • "Backend authentication failed" → Check API keys configuration
  • "File not found" → Verify file paths relative to workdir:
  • "Circular dependency" → Restructure task dependencies (no cycles)
  • "Context size exceeded" → Use files-mode: ref or load fewer files

Summary

memex-cli enables AI-powered development workflows with:

  • Multi-backend support (codex, claude, gemini)
  • Parallel and sequential task execution
  • Resume capability for iterative development
  • Flexible file loading with glob patterns
  • Structured output (text, JSONL)

Start with examples/basic-task.md, then explore advanced patterns in references/.