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Generate Claude Code Workflows using Spec Driven Development approach

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Generate Claude Code Workflows using Spec Driven Development approach

I have been using a Spec-Driven Development approach for all mid+ size coding tasks since Feb 2026: https://news.ycombinator.com/item?id=48231575 . One of the reasons for developing my own plugin (sddw - spec driven development workflow https://github.com/sermakarevich/sddw/ ) was to adjust it to my specific needs and the typical size of the features I build. Since then, this approach (sddw) has been presented at a few companies, including Google Poland. One of the conclusions from these conversations was that some teams would also like to adapt the plugin to their specific needs, the size of their projects, and even to non-coding tasks such as marketing research. So I built Claude Code Workflow (CCW). It's a generator for linear Spec-Driven Development (SDD) workflow plugins for Claude Code. You define a workflow in a single configs/<name>.yaml file, and CCW regenerates all commands, install scripts, and plugin manifests automatically. You just need to add the instructions required for each step of your workflow. Every step of the workflow produces a spec artifact, and every subsequent step is aware of the artifacts produced previously. You /clear your context after each step. Everything is SDD-based and works for any kind of multi-step task or workflow. Repo: https://github.com/sermakarevich/ccw

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, google, new · Missing: mac, agents, macos
89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Strong signals: including · Missing: supports, reddit linkedin, podcasting
49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io, including · Missing: https docs, excited, just released
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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