Use after gsd-code-review has written REVIEW.md, when you want its Critical and Warning findings fixed. Spawns the fixer agent, commits each fix atomically and writes REVIEW-FIX.md (--all, --auto to iterate).
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See how to installReview the instructions the agent will receive before you install.
Arguments:
--all (optional) — include Info findings in fix scope (default: Critical + Warning only)--auto (optional) — enable fix + re-review iteration loop, capped at 3 iterationsOutput: {padded_phase}-REVIEW-FIX.md in phase directory + inline summary of fixes applied </objective>
<execution_context> @$HOME/.claude/get-shit-done/workflows/code-review-fix.md </execution_context>
<context> Phase: $ARGUMENTS (first positional argument is phase number)Optional flags parsed from $ARGUMENTS:
--all — Include Info findings in fix scope. Default behavior fixes Critical + Warning only.--auto — Enable fix + re-review iteration loop. After applying fixes, re-run code-review at same depth. If new issues found, iterate. Cap at 3 iterations total. Without this flag, single fix pass only.Context files (CLAUDE.md, REVIEW.md, phase state) are resolved inside the workflow via gsd-tools init phase-op and delegated to agent via config blocks.
</context>
Execute the code-review-fix workflow from @$HOME/.claude/get-shit-done/workflows/code-review-fix.md end-to-end.
The workflow (not this command) enforces these gates:
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Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents with tracing, configuring LightningStore, implementing reward functions, or optimizing prompts with RL/APO algorithms.
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Post-run self-evaluation system that scores agent output on correctness, clarity, actionability, and conciseness. Use after /team runs, skill executions, or when explicitly asked to evaluate output quality.
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Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awareness. Triggers: marketing video, ad video, promo video, commercial, brand video, product video, explainer video, ad creative, video ad, facebook ad video, youtube ad, instagram ad, tiktok ad, promotional video, launch video
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Use when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.
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Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
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Use when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls.
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