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cautious-computing-machine--sdlc-plugin
cautious-computing-machine--sdlc-plugin contains 13 collected skills from iamladi, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Generates a narrative walkthrough of AI-authored code changes. Use after implementation to explain what changed, why, and how it behaves.
Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing. Resolves the latest flagship model from the model registry.
Evaluate plugin commands, agents, and skills against Anthropic Constitution principles. Score alignment on reasoning-based vs rule-based instruction spectrum, identify improvement opportunities. Use when the user wants to audit, score, or review the quality of a command, agent, or skill — e.g. "review this skill", "audit this command", "is this agent well-written", "score this against constitutional principles", or "check this for rule-based patterns".
Grilling session that challenges a plan against the target repo's existing domain model, sharpens terminology, and updates CONTEXT.md + ADRs inline as decisions crystallise. Invoked by /sdlc:plan at step 3.5 to keep architecture aligned with documented language before the plan is drafted.
Post-merge cleanup workflow. Detects PR merge, switches to main, pulls latest, runs tests, and removes worktree if exists. Use after PR is merged to clean up.
Use when the user asks to run Gemini CLI for code review, plan review, or big context (>200k) processing. Ideal for comprehensive analysis requiring large context windows. Resolves the latest flagship model from the model registry.
Evaluates agent judgment quality through scenario-based testing in-conversation. Use when the user wants to test, validate, or stress-test an agent, skill, or command definition — e.g. "test this agent", "evaluate this skill", "does this prompt handle edge cases", "check this agent's judgment", or after writing or modifying any agent/skill/command .md file.
Interactive skill that diagnoses and transforms system prompts from rule-based to reasoning-based using Constitutional AI principles. Use when the user wants to improve, rewrite, or transform any system prompt, command, agent, or skill — e.g. "improve this prompt", "make this less rigid", "transform this rule-based command", "optimize this agent", or "this skill keeps breaking on edge cases".
TDD enforcement during implementation. Reads `tdd:` setting from CLAUDE.md. Modes - strict (human approval for escape), soft (warnings), off (disabled). Auto-invoked by /implement.
Write or review tests following Kent C. Dodds testing principles - flat structure, composable setup, disposable fixtures. Use when the user asks to write tests, review tests, or convert legacy tests.
Re-resolve the model registry by querying OpenAI Codex cache, Google AI API, and Oracle CLI. Use when models feel stale or after a major model release.
Search X/Twitter for real-time developer discourse, product feedback, community sentiment, and expert opinions. Use when user says "x search", "search x for", "search twitter for", "what are people saying about", or needs recent X discourse for context (library releases, API changes, product launches, industry discussion). Also use when researching a library, framework, API, or product to supplement web search with real-time community signal — e.g. "research Bun", "what do devs think of Hono", "is Turso production-ready".
Conducts depth-first interview walking a plan's decision tree with mandatory recommendations. Use when user wants to stress-test a design, get grilled on a plan, or says "interview me" / "grill me" / "walk me through this".