product-launch-validator

product-launch-validator is a skill for Claude Code, Codex from TashanGKD/tashan-cursor-skills. It costs 136 tokens per session (1,850 once invoked), scanned A, original, MIT.

A pre-launch checklist for checking whether a new product fits an existing knowledge system, work structure, and technical setup.

In plain words
What is it for?
Use it to assess a new product or independent subsystem before committing to implementation.
Why use it?
It reveals missing domains, skills, rules, or technical support before development begins.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw; mentions OpenCode.

Good fit Use it to assess a new product or independent subsystem before committing to implementation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tashangkd/tashan-cursor-skills/product-launch-validator
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.

Any agent
npx skills add TashanGKD/tashan-cursor-skills --skill product-launch-validator
Clone the repo
git clone --depth 1 https://github.com/TashanGKD/tashan-cursor-skills

Made for: Claude Code, Codex.

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 product-launch-validator

README.md
[![agentmods](https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/product-launch-validator/github.svg)](https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/product-launch-validator)
Your own site
<a href="https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/product-launch-validator"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/product-launch-validator/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for product-launch-validator

Your own site · 80×15
<a href="https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/product-launch-validator"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/product-launch-validator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 136 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,850 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00136 $0.01850
Opus 5 $0.00068 $0.00925
Sonnet 5 $0.00027 $0.00370
Haiku 4.5 $0.00014 $0.00185

Measured 8d ago against content hash 74bf1936cfc3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

product-launch-validator scanned grade A with 0 findings 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 8d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/product-launch-validator/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

新产品三大闭环兼容性验证(product-launch-validator)

关系类型:validates → 三大闭环架构蓝图(在立项时验证 Loop 1/2/3 的兼容性) 触发时机:role-产品经理 激活之前(可选但推荐) 设计依据:三大闭环架构蓝图 §差距清单「新产品/场景加入时兼容性检查:❌缺失」


使用场景

何时触发

  • 启动一个全新的产品项目(而非现有产品的迭代)
  • 在现有生态中添加新的独立场景或子系统
  • 不确定「这个新产品和我们现有的 Skill 体系/认知结构/部署架构是否兼容」

不应触发

  • 现有产品的功能迭代(走 role-产品经理 迭代模式即可)
  • 纯 Skill 或 Rule 的新建(走 skill-designer)

激活后立即执行

Step 1  收集新产品基本信息
        询问用户(如果上下文不明确):
        「请描述新产品的:
           1. 核心功能一句话描述
           2. 主要用户群体
           3. 依赖的技术栈(前端框架/后端语言/AI能力)
           4. 与现有产品的关系(完全独立/共享账号/共享数据库)」
        
        确认后继续。

Step 2  Loop 1 检查:Skill 体系兼容性
        Read: .cursor/skills/skill-index/SKILL-INDEX.md(快速扫描,了解已有能力覆盖)
        
        检查三项:
        ① 新产品的开发流程(PM→架构→前后端→测试→部署)是否有现有 Skill 完整覆盖?
           → 对每个阶段:现有 Skill 是否支持新产品的特殊需求(如新技术栈/新部署模式)
        ② 新产品涉及的领域(如:学术画像/科研工具/AI编辑器),是否有对应的域节点
           在 DOMAIN-REGISTRY 中已定义?
           → 若无 → 标记「需要在 DOMAIN-REGISTRY 新增工作域」
        ③ 新产品是否引入了新的技术边界(如:新AI模型/新第三方服务/新部署架构)
           需要新建 Skill 或 Rule 才能安全执行?

Step 3  Loop 2 检查:认知根对齐
        Read: _内部总控/认知结构/L0_大脑总地图.md
        Read: _内部总控/认知结构/L1.5_底层原则层/底层原则库.md(候选原则部分)
        
        检查两项:
        ① 新产品的核心价值主张,在现有 L1 系统性文档中是否有对应的认知根?
           → 具体:L1 的哪篇文档支撑了「为什么要做这个产品」的判断?
           → 若无 → 标记「产品认知根缺失:建议先用 cognitive-capture-fragment 
             记录洞见,再用 cognitive-update-knowledge 补充 L1」
        ② 新产品的设计假设,是否与已确认的 L1.5 原则(P1/P2/...)兼容?
           → 扫描候选原则,识别可能与新产品设计有张力的原则

Step 4  Loop 3 检查:场景投射兼容性
        Read: _内部总控/skill-system-design/DOMAIN-REGISTRY.md(快速了解已有工作域)
        Read: _内部总控/开发规范/AI调用服务器助手接口规范.md(如有,了解技术约束)
        
        检查两项:
        ① 新产品的工作域(工作任务/工作产物/项目结构)是否已在 DOMAIN-REGISTRY 的
           五域定义之内?
           → 若无 → 标记「需要在 DOMAIN-REGISTRY 中新增节点」并给出建议定义
        ② 新产品的技术架构(账号体系/数据库/部署位置)是否与现有服务兼容?
           → 特别检查:是否重用现有账号体系?是否加入 tashan-shared 网络?

Step 5  输出兼容性报告
        
        「━━ 立项兼容性检查报告 ━━
          新产品:[名称]
          
          Loop 1 Skill 体系:
          ✅ 已覆盖:[列举]
          ⚠️ 需补充:[列举缺口 + 建议行动]
          
          Loop 2 认知根:
          ✅ 有认知根:[L1 文档名]
          ⚠️ 认知根缺失:[建议:先记录 L2 碎片或更新 L1]
          
          Loop 3 工作域:
          ✅ 现有域覆盖:[域名]
          ⚠️ 需要新增域节点:[建议定义]
          
          技术兼容性:[兼容 / 需要新建 Rule:前端品牌守门/API兼容检查/...]
          ─────────────────────────────
          
          综合判断:
          ✅ 完全兼容 → 可直接触发 role-产品经理
          ⚠️ 有缺口但可并行补齐 → 建议按「建议行动」顺序处理后再启动开发
          ❌ 结构性不兼容 → 必须先解决阻塞项才能立项
          
          [立即触发 role-产品经理] [先处理缺口]」

Read the full file on GitHub · 134 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. 8d ago First seen · 134 lines · 136 tokens per session scan A 74bf1936cfc3

Subscribe to this mod's changes

product-launch-validator is a skill published in the GitHub repository TashanGKD/tashan-cursor-skills (20 stars, last pushed 5mo ago), licensed MIT. It adds 136 tokens to every session and 1,850 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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