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lsa03

Parallel Responder

by Amber03 · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
417
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0
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1
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1
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Install in OpenClaw
/install parallel-responder
Description
并行回复助手 - 让 AI 回复不再等待。支持任务分类、时间预估、并行执行、进度汇报。 简单任务直接回复,中等任务执行 + 汇报,复杂任务启动子 agent 并行处理。 Parallel Responder - Zero-wait AI responses. Task classification, time e...
Usage Guidance
This skill appears to be a reasonable orchestrator conceptually, but there are important mismatches between what the docs promise and what the code actually does. Before installing or enabling it: 1) Ask the author to explain and show the exact implementation for spawning sub‑agents and for progress reporting (what platform APIs are called and what permissions are required). 2) Confirm where results are stored (the README example shows /root/openclaw/… — that implies filesystem writes and elevated access). 3) Require the skill to declare any required env vars/credentials or platform capabilities (sessions_spawn, sessions_send) and provide safe defaults or opt-in consent for persistent storage and learning. 4) If you run it, do so in a sandboxed environment first because the documented behavior (starting child agents, saving files) could enable broader access than the in‑memory stubs suggest. If the author provides a clarified integration plan showing no external or privileged side effects, the inconsistencies would be resolved; until then treat the skill with caution.
Capability Analysis
Type: OpenClaw Skill Name: parallel-responder Version: 1.0.0 The skill is classified as suspicious due to its reliance on the OpenClaw platform's `sessions_spawn` mechanism, as described in `SKILL.md` and implemented in `scripts/parallel-executor.js`. This feature allows the skill to launch 'sub-agents' and pass user messages to them for 'complex tasks'. While `sessions_spawn` is an intended platform capability, passing user-controlled input to dynamically spawned agents without explicit sanitization or strict sandboxing creates a significant attack surface, potentially leading to Remote Code Execution (RCE) if the sub-agents are vulnerable to prompt or command injection. There is no direct evidence of intentional malicious behavior within the provided files, but the high-risk delegation mechanism warrants a 'suspicious' classification.
Capability Assessment
Purpose & Capability
The declared purpose (classify tasks, estimate time, run tasks in parallel, report progress) matches the included modules (classifier, estimator, executor, reporter). However the SKILL.md and README mention integration points (OpenClaw Gateway, sessions_spawn, sessions_send) and saving artifacts to paths like /root/openclaw/... which are not implemented in the code. That mismatch suggests missing integration glue rather than a simple, self-contained implementation.
Instruction Scope
SKILL.md describes starting child agents and saving results to filesystem paths, and implies calling platform services (sessions_spawn / sessions_send) for spawning and reporting. The runtime instructions do not declare required permissions or environment variables for those operations, and the code only stubs sub‑agent behavior (creates an in‑memory task entry) without actually calling any sessions_spawn/send APIs or writing files. This is scope creep: the skill promises actions (spawning agents, persistent storage) that are not implemented or justified in the files.
Install Mechanism
There is no install spec and no downloads; risk from installation is low. The skill ships as code files (JS modules) and appears to be instruction-only with included source — nothing is fetched from external URLs during install.
Credentials
The skill declares no required environment variables, credentials, or config paths. The implementation also does not access environment secrets. That is proportionate to the provided code. Note: if the skill were wired to sessions_spawn / sessions_send or to write files, additional permissions or paths would be required but those are not declared.
Persistence & Privilege
The skill is not forcibly always-enabled and does not request special platform privileges in metadata. However SKILL.md and examples imply persistent behavior (learning/history, saving drafts to /root) and spawning child agents — both of which, if implemented, would raise privilege concerns (access to filesystem, ability to create autonomous sub-agents). At present the code keeps histories in memory only.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install parallel-responder
  3. After installation, invoke the skill by name or use /parallel-responder
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Parallel Responder v1.0.0 - Initial Release - Implements intelligent task classification (simple, medium, complex) based on keywords and estimated time. - Adds a time estimator to predict task duration and handle user expectations. - Supports parallel execution strategies, including spawning sub-agents for complex tasks. - Provides real-time progress reporting and updates (immediate reply, scheduled progress reports). - Features adaptive learning to optimize classification thresholds using historical data.
Metadata
Slug parallel-responder
Version 1.0.0
License
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Parallel Responder?

并行回复助手 - 让 AI 回复不再等待。支持任务分类、时间预估、并行执行、进度汇报。 简单任务直接回复,中等任务执行 + 汇报,复杂任务启动子 agent 并行处理。 Parallel Responder - Zero-wait AI responses. Task classification, time e... It is an AI Agent Skill for Claude Code / OpenClaw, with 417 downloads so far.

How do I install Parallel Responder?

Run "/install parallel-responder" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Parallel Responder free?

Yes, Parallel Responder is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Parallel Responder support?

Parallel Responder is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Parallel Responder?

It is built and maintained by Amber03 (@lsa03); the current version is v1.0.0.

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