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symphonysymphony 开发

Agent Skill

symphony 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

11,668

周安装

472

GitHub Stars

公开资料未说明

下载量

3,663
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:symphony(symphony 开发)
来源仓库:https://github.com/ivangdavila/symphony
安装命令:
openclaw skills install symphony
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install symphony

简介

使用独立的问题工作区、工作流程合同和无人值守的 Codex 编排为 Linear 项目设置和运行 OpenAI Symphony。

SKILL.md

name
OpenAI Symphony
slug
symphony
version
1.0.0
homepage
https://clawic.com/skills/symphony
description
Set up and run OpenAI Symphony with isolated issue workspaces, workflow contracts, and unattended Codex orchestration for Linear projects.
changelog
Initial release with workflow templates, runbook guidance, and safety guardrails for operating Symphony in trusted environments.
metadata
{"clawdbot":{"emoji":"S","requires":{"bins":["git","codex"],"env":["LINEAR_API_KEY","OPENAI_API_KEY","GITHUB_TOKEN"],"config":["~/symphony/"]},"os":["darwin","linux","win32"],"configPaths":["~/symphony/"]}}

Setup

On first use, read setup.md and establish integration boundaries before proposing commands or workflow edits.

When to Use

Use this skill when the user wants an unattended orchestration service that reads Linear issues, creates per-issue workspaces, and drives Codex in app-server mode until work reaches review or done states. It is optimized for Symphony rollout, workflow authoring, safety hardening, and day-2 operations.

Architecture

Memory lives in ~/symphony/. See memory-template.md for setup.

~/symphony/
|-- memory.md                # Activation policy, environment profile, and operating defaults
|-- workflow-notes.md        # WORKFLOW.md decisions, state map, and prompt policy
|-- incidents.md             # Runtime failures, retries, and mitigations
`-- run-history.md           # Launch evidence, validations, and release notes

Quick Reference

Use the smallest relevant file for the task.

TopicFile
Setup and activation behaviorsetup.md
Memory template and status valuesmemory-template.md
Upstream spec map and implementation checkpointsSPEC.md
Starter workflow contract used by the serviceWORKFLOW.md
Bootstrap and launch runbooksetup-runbook.md
WORKFLOW.md contract templateworkflow-template.md
Security hardening and trust checkssafety-guardrails.md
Incident triage and recoveryincident-playbook.md

Requirements

  • Repository access for the target project and a safe workspace root
  • Linear personal API key in LINEAR_API_KEY
  • OpenAI auth for Codex (OPENAI_API_KEY or equivalent codex login session)
  • Git remote credentials (GITHUB_TOKEN or SSH key access) for clone/fetch/push hooks
  • codex binary with app-server support
  • git for workspace bootstrap hooks
  • explicit user approval of target environment before unattended operation
  • Trusted environment policy approved by the user before unattended operation

Core Rules

1. Treat SPEC.md as the Contract

When implementation details are unclear, align with the upstream Symphony specification first. Do not invent incompatible state models, config keys, or agent-runner behavior.

2. Keep WORKFLOW.md Repository-Owned and Validated

All orchestration policy must live in versioned WORKFLOW.md front matter plus prompt body. Validate YAML and template variables before launch, because invalid workflow files halt dispatch.

3. Enforce Per-Issue Workspace Isolation

Map each issue identifier to a dedicated workspace key and run Codex only inside that directory. Never execute agent work in shared roots or outside the configured workspace boundary.

4. Respect State-Driven Orchestration

Dispatch only active tracker states, stop sessions on terminal states, and preserve idempotent recovery after restarts. A run can end in a workflow-defined handoff state, not only Done.

5. Autonomy Requires Explicit Environment Approval

Before enabling unattended operation, confirm the repository, tracker project, and workspace root are approved by the user. Start with conservative policy (approval_policy: on-request) and test-project rollout before broadening scope.

6. Apply Bounded Concurrency, Retries, and Safe Hooks

Use explicit concurrency ceilings and exponential backoff for transient failures. Retries must resume from existing workspace state instead of repeating completed investigation work. Allow only deterministic hooks that stay inside the issue workspace and avoid secret exfiltration patterns (curl | sh, arbitrary uploads, or parent-directory deletes).

7. Preserve Observability and Safety Evidence

Record launch config, workspace path, tracker state transitions, validation proof, and token/runtime metrics for every run. Operators must be able to reconstruct what happened without rerunning the issue.

Common Traps

  • Copying sample workflow statuses without matching the team's Linear workflow -> agents never dispatch or never stop.
  • Running hooks that write outside the issue workspace -> cross-issue contamination and unsafe side effects.
  • Using prompt templates with unknown variables -> attempt failures at render time.
  • Treating retries as fresh runs -> duplicated commits, repeated comments, and wasted tokens.
  • Starting unattended runs in untrusted environments -> elevated risk of accidental destructive actions.
  • Ignoring terminal-state cleanup -> stale workspaces consume disk and hide old state.

External Endpoints

EndpointData SentPurpose
https://api.linear.app/graphqlIssue metadata, state queries, and workflow updatesTracker polling, reconciliation, and issue-level orchestration
https://api.openai.comCodex app-server requests and model output payloadsAgent execution for implementation turns
https://github.comRepository clone/fetch/push traffic defined by workspace hooksPrepare and update per-issue code workspaces

No other data is sent externally unless the user adds additional integrations.

Security & Privacy

Data that leaves your machine:

  • Linear issue context required for dispatch and reconciliation
  • Codex request/response payloads needed for agent execution
  • Git remote traffic required by repository hooks

Data that stays local:

  • Orchestration notes and memory files in ~/symphony/
  • Workspace content under the configured root
  • Local logs and runtime snapshots

This skill does NOT:

  • bypass declared sandbox or approval policies
  • execute undeclared external endpoints
  • approve ambiguous hook scripts automatically
  • modify its own SKILL.md

Trust

This skill depends on OpenAI Codex APIs, Linear APIs, and your configured Git remote. Only install and run it if you trust those services with your repository and issue data.

Related Skills

Install with clawhub install <slug> if user confirms:

  • agent - Improve single-agent execution quality for scoped implementation tasks.
  • agents - Coordinate multiple agents with explicit ownership and handoff boundaries.
  • agentic-engineering - Enforce high-rigor workflows for autonomous software delivery.
  • workflow - Design robust repeatable workflows with clear gates and status transitions.
  • memory - Persist durable context and operating preferences across sessions.

Feedback

  • If useful: clawhub star symphony
  • Stay updated: clawhub sync

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

85.22%
按下载量换算3,122

安全审计

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可疑

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通过

Static analysis

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权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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