pm-release

pm-release is a skill for Claude Code, Codex from konglong87/superPM. It costs 60 tokens per session (5,007 once invoked), scanned A, original, MIT.

A release-planning workflow for preparing software to go live, including checks, deployment choices, timing, and rollback conditions.

In plain words
What is it for?
Use it to create launch checklists, choose release and environment strategies, plan release windows, and define rollback triggers.
Why use it?
It reduces the risk of releasing an untested version or lacking a clear response when production problems appear.

Skill for Claude CodeCodex

Part of the super-pm plugin — 55 skills, 1 hook shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/konglong87/superpm/pm-release
Any agent
npx skills add konglong87/superPM --skill pm-release
Clone the repo
git clone --depth 1 https://github.com/konglong87/superPM

Made for: Claude Code, Codex.

Or install super-pm, the plugin that ships this one along with the rest of its 55 skills, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pm-release

README.md
[![agentmods](https://agentmods.dev/badge/skills/konglong87/superpm/pm-release.svg)](https://agentmods.dev/skills/konglong87/superpm/pm-release)
Your own site
<a href="https://agentmods.dev/skills/konglong87/superpm/pm-release"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-release.svg" alt="Measured on agentmods" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,007 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00060 $0.05007
Opus 5 $0.00030 $0.02504
Sonnet 5 $0.00012 $0.01001
Haiku 4.5 $0.00006 $0.00501

Measured 5d ago against content hash 0da178030423, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pm-release scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -I https://app.example.com/health
skills/04-risk-management/pm-release/SKILL.md · 670 lines

How it starts

The opening of the file, as written. The whole thing — 670 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble

bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
mkdir -p docs/04-风控管理

echo "🚀 上线执行方案制定工具已启动"

跨 Agent 交互规则

当流程要求与用户交互时:

  1. 如果当前环境支持 AskUserQuestion,使用 AskUserQuestion(最佳体验)。
  2. 如果当前环境不支持 AskUserQuestion,必须用普通聊天消息提出同样问题。
  3. 一次只问一个问题。
  4. 提问后必须停止当前回合,等待用户回答(STOP and WAIT)。
  5. 不得在用户回答前生成文档、写入 docs。
  6. 已有 docs 文件不能替代本轮用户回答。

执行流程

步骤 1: 确定上线策略

使用 AskUserQuestion:

📦 上线策略选择

选择本次上线的方式:

A) 全量发布(一次性上线所有用户) B) 灰度发布(逐步放开用户比例) C) 蓝绿部署(新旧版本并行) D) 金丝雀发布(小流量验证)

继续询问:

🌍 环境部署策略

需要在哪些环境部署?

A) 仅生产环境 B) 测试环境 → 生产环境 C) 开发环境 → 测试环境 → 预发布环境 → 生产环境 D) 自定义环境流程

步骤 2: 制定上线检查清单

使用 AskUserQuestion:

✅ 上线检查项

必须检查哪些项目?(可多选)

A) 功能测试(核心功能验证) B) 性能测试(压力测试、容量验证) C) 安全检查(漏洞扫描、权限验证) D) 兼容性测试(多端、多浏览器) E) 数据备份(数据库、配置文件) F) 监控告警(日志、指标、告警规则) G) 文档完备(用户手册、运维文档) H) 全部检查

步骤 3: 规划发布时间

使用 AskUserQuestion:

⏰ 发布时间窗口

选择合适的发布时间:

A) 工作日白天(便于快速响应问题) B) 工作日夜间(用户量少,影响小) C) 周末夜间(最低峰时段) D) 根据业务特点灵活选择

继续询问:

📅 发布节奏

发布频率是?

A) 单次发布(一次性完成) B) 分阶段发布(多个版本逐步上线) C) 持续发布(多次迭代,持续优化)

步骤 4: 设计回滚方案

使用 AskUserQuestion:

🔙 回滚触发条件

什么情况下需要回滚?

A) 严重Bug导致功能不可用 B) 性能严重下降(响应时间、错误率) C) 用户投诉激增 D) 数据异常(关键指标暴跌) E) 以上全部情况

继续询问:

⏱️ 回滚时间要求

从决定回滚到完成回滚,最长可接受时间:

A) 5分钟内(快速回滚) B) 15分钟内(标准回滚) C) 30分钟内(慢速回滚) D) 1小时内(可接受)

步骤 5: 规划通知机制

使用 AskUserQuestion:

📢 上线通知对象

需要通知哪些人?(可多选)

A) 内部团队(产品、研发、测试、运营) B) 管理层(项目发起人、部门负责人) C) 外部用户(发布公告、更新日志) D) 合作伙伴(第三方服务、渠道方) E) 客服团队(提前准备FAQ)

步骤 6: 生成上线执行方案

使用 Write 工具生成 docs/04-风控管理/上线执行方案.md


Subagent 并行加速(v2.0.0 新增)

利用 Agent 工具并行执行独立子任务,大幅缩短总执行时间。

可并行子任务

当步骤1-3的用户信息收集完成后,以下两个任务可以并行执行:

子任务 说明
检查清单编排 基于上线策略和检查项,自动生成完整上线检查清单
回滚方案设计 根据回滚触发条件和时间要求,输出回滚操作步骤

触发方式

在步骤6生成文档前,使用 Agent 工具激活子任务并行执行。

V1 vs V2 对比

维度 V1.1.0(串行) V2.0.0(Subagent并行) 节省
检查清单 用户逐一确认检查项 Agent并行生成完整清单 约3轮交互
回滚方案 依次询问回滚细节 Agent自动输出回滚步骤 约2轮交互
通知机制设计 逐个问询通知对象 Agent并行编排通知方案 约2轮交互
总交互轮次 约12-15轮 约6-8轮 减少50%+
耗时估算 12-18分钟 6-9分钟 节省约8分钟

Read the full file on GitHub · 670 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 670 lines · 60 tokens per session scan A 0da178030423

Subscribe to this mod's changes

pm-release is a skill published in the GitHub repository konglong87/superPM (61 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 5,007 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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