Run the continuous-discovery loop — score the weekly cadence (Torres), act on the named gap, lint the Opportunity Solution Tree as the machine gate, and keep th
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-claude-skills-8675c63dfad4 ,按照其中的说明把「cs-product-loop」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Inputs (defaults: discovery_log.json and ost.json in the workspace; shapes in
product-team/skills/product-skills/assets/):
$ARGUMENTS
python3 product-team/skills/product-skills/scripts/discovery_cadence_tracker.py --input discovery_log.json
Exit 5 (< 2 interviews): there is no cadence to measure — help the user book the
first two weekly touchpoints and write the outcome statement; stop there.next_loop_action is the choice. Typical actions: book the
missing weekly touchpoint · re-anchor the interview guide on the outcome · test the
top untested assumption (route to product-discovery's assumption_mapper to rank).python3 product-team/skills/product-skills/scripts/ost_linter.py --input ost.json
Exit 2 → fix the listed O1–O5 violations before the tree may drive any roadmap or
experiment. Then re-run the cadence tracker and confirm the health score did not
drop.discovery_log.json (interview/test entries) and ost.json;
note the health score in the digest so the trend is visible across iterations.experiment-designer
(A/B gate) or product-manager-toolkit (PRD with eval spec if the feature is
AI-powered).