▸case-01 Our backend team is using specification-driven development, but we frequently hit mismatches between our feature spec docs and the AI-generated code output. Please design an iterative development and review cycle that establishes traceability between feature requirements and generated code, including a systematic approach to refine prompts when output drifts from specs. | fail→pass | 23,293 | 22,073 | -5% | 1 | 1 | 0% | 3,748 | 4,962 | +32% | 0 | 0 | — |
▸case-02 We are building a hackathon MVP in 12 hours with no existing specification files. We need to rapidly assemble a working demo using AI assistance without getting slowed down by documentation overhead. How should we structure our specification workflow? | fail→fail | 15,092 | 13,764 | -9% | 1 | 1 | 0% | 2,313 | 3,465 | +50% | 0 | 0 | — |
▸case-03 Our production web server is throwing a null pointer exception on the checkout route due to an edge case in memory state. We need an immediate fix deployed in 20 minutes. How should we start writing the feature spec and update our multi-folder CLAUDE.md files before fixing the bug? | pass→pass | 11,276 | 8,641 | -23% | 1 | 1 | 0% | 1,655 | 2,583 | +56% | 0 | 0 | — |
▸case-04 Our engineering organization operates strictly under a code-first, Test-Driven Development methodology with no specification docs or Spec-Kit artifacts. We want to refactor our authentication service by writing unit tests first. Please outline how to enforce a specification-first workflow for this service refactor. | fail→fail | 15,621 | 16,500 | +6% | 1 | 1 | 0% | 2,539 | 4,008 | +58% | 0 | 0 | — |
▸case-05 We have a monorepo containing a React frontend in `/apps/web` and a Python FastAPI backend in `/apps/api`. We want AI assistants to follow repository-wide conventions while respecting folder-specific rules. How should we structure configuration files across these directories? | fail→pass | 17,861 | 10,698 | -40% | 1 | 1 | 0% | 3,046 | 3,062 | +1% | 0 | 0 | — |
▸case-06 In our multi-package repository, shared TypeScript interfaces in `/packages/types` are imported by both `/apps/web` and `/apps/mobile`. We want AI coding sessions in `/apps/web` to be aware of the dependency on `/packages/types`. What should be documented in the repository configuration files? | fail→pass | 12,922 | 8,707 | -33% | 1 | 1 | 0% | 2,270 | 2,765 | +22% | 0 | 0 | — |
▸case-07 Our team is standardizing specification files across multiple microservices to ensure AI coding agents read them consistently. What structural elements and naming practices should be established for specification artifacts? | pass→pass | 18,077 | 14,774 | -18% | 1 | 1 | 0% | 2,911 | 3,632 | +25% | 0 | 0 | — |
▸case-08 We frequently receive vague user stories like 'Make the checkout page faster' which leads AI generators to write random optimizations. How should we enforce specification quality before handing specs to AI coding tools? | pass→pass | 14,649 | 15,039 | +3% | 1 | 1 | 0% | 2,207 | 3,595 | +63% | 0 | 0 | — |
▸case-09 When invoking Claude Code to build a new payment endpoint, how should we instruct the tool to ensure it does not hallucinate arbitrary parameters or ignore established architecture? | pass→pass | 13,799 | 10,895 | -21% | 1 | 1 | 0% | 2,109 | 2,898 | +37% | 0 | 0 | — |
▸case-10 During code reviews of AI-generated pull requests, how can we confirm that the implemented code accurately satisfies feature requirements and does not introduce out-of-scope logic? | pass→pass | 16,983 | 13,809 | -19% | 1 | 1 | 0% | 2,549 | 3,394 | +33% | 0 | 0 | — |
▸case-11 Our prompts for AI coding agents occasionally produce incorrect variable names or miss error handling. How should we systematically refine prompts over time rather than treating each prompt as a one-off attempt? | fail→pass | 15,660 | 15,579 | -1% | 1 | 1 | 0% | 2,355 | 3,646 | +55% | 0 | 0 | — |
▸case-12 We are initiating a greenfield billing service and want to follow a strict specification-first approach with AI implementation. What sequence of steps should we follow from project start to code delivery? | pass→pass | 19,948 | 17,414 | -13% | 1 | 1 | 0% | 3,055 | 4,090 | +34% | 0 | 0 | — |
▸case-13 While implementing a complex search feature with AI assistance, we discovered that an API specification missed an edge case for empty filter arrays. What is the proper workflow pattern to address this gap? | pass→pass | 11,650 | 8,307 | -29% | 1 | 1 | 0% | 1,801 | 2,536 | +41% | 0 | 0 | — |
▸case-14 We have 10 micro-services in a single workspace. Developers are creating custom AI config files in each service folder, leading to conflicting linting and build command definitions across the workspace. How should configuration consistency be enforced? | fail→pass | 14,404 | 14,878 | +3% | 1 | 1 | 0% | 2,206 | 3,779 | +71% | 0 | 0 | — |
▸case-15 Our project requires functional requirements, technical architecture diagrams, and REST API contracts. How should specification formatting be organized to accommodate these different artifact types without creating mess? | pass→fail | 19,148 | 16,454 | -14% | 1 | 1 | 0% | 2,672 | 4,031 | +51% | 0 | 0 | — |
▸case-16 When auditing AI-generated code for compliance with feature specifications, what quality assurance checks should be performed regarding code robustness? | pass→pass | 16,017 | 11,040 | -31% | 1 | 1 | 0% | 2,317 | 2,703 | +17% | 0 | 0 | — |
▸case-17 Different team members write drastically different prompts for Claude Code, leading to inconsistent code quality across modules. How can the team unify prompt effectiveness? | fail→fail | 15,849 | 12,442 | -21% | 1 | 1 | 0% | 2,408 | 3,083 | +28% | 0 | 0 | — |
▸case-18 An AI coding agent fails or generates incorrect implementations because a specification given to it was partially incomplete. What error handling strategy should be applied in the development workflow? | pass→pass | 13,075 | 9,987 | -24% | 1 | 1 | 0% | 2,037 | 2,562 | +26% | 0 | 0 | — |
▸case-19 Our development team is expanding from 2 to 15 engineers using Claude Code and Spec-Kit specifications. What workflow measures ensure consistent application of spec-driven processes as new developers join? | pass→pass | 17,621 | 16,136 | -8% | 1 | 1 | 0% | 2,690 | 3,714 | +38% | 0 | 0 | — |
▸case-20 We need a verification procedure at the end of a sprint to ensure that AI-generated deliverables meet project goals. What should the output of this verification include? | pass→pass | 13,540 | 10,803 | -20% | 1 | 1 | 0% | 2,061 | 2,796 | +36% | 0 | 0 | — |
▸case-21 Our team is evaluating whether we are ready to adopt a Spec-Kit and Claude Code workflow. What prerequisites must be satisfied before implementing this conceptual workflow? | fail→pass | 16,428 | 8,382 | -49% | 1 | 1 | 0% | 2,443 | 2,449 | +0% | 0 | 0 | — |
▸case-22 Writing detailed specifications for every tiny feature risks slowing down our sprint velocity. How should a spec-driven AI development workflow optimize for performance and speed without losing quality? | pass→pass | 15,681 | 10,419 | -34% | 1 | 1 | 0% | 2,305 | 2,770 | +20% | 0 | 0 | — |