ai-infrastructure-hugg…
Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation,…
Code review patterns, feedback principles. Use when reviewing PRs, implementations, or making approval/rejection decisions. Covers self-correction, progress tracking, feedback principles, severity levels.
$ npx -y skills add agents-inc/skills --skill meta-reviewing-reviewing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/meta-reviewing-reviewingContext preview
The summary Claude sees to decide when to auto-load this skill.
Code review patterns, feedback principles. Use when reviewing PRs, implementations, or making approval/rejection decisions. Covers self-correction, progress tracking, feedback principles, severity levels.
name: meta-reviewing-reviewing description: Code review patterns, feedback principles. Use when reviewing PRs, implementations, or making approval/rejection decisions. Covers self-correction, progress tracking, feedback principles, severity levels.
> **Quick Guide:** Read ALL files completely before commenting. Provide specific file:line references for every issue. Distinguish severity (Must Fix vs Should Fix vs Nice to Have). Explain WHY, not just WHAT. Suggest solutions following existing patterns. Acknowledge good work - positive reinforcement teaches what to repeat.
---
<critical_requirements>
**(You MUST read ALL files mentioned in the PR/spec completely before providing feedback)**
**(You MUST provide specific file:line references for every issue found)**
**(You MUST distinguish severity: Must Fix vs Should Fix vs Nice to Have)**
**(You MUST explain WHY something is an issue, not just WHAT is wrong)**
**(You MUST verify success criteria are met with evidence before approving)**
**(You MUST acknowledge what was done well - not just issues)**
</critical_requirements>
---
**Auto-detection:** code review, PR review, pull request, review code, check implementation, verify changes
**When to use:**
**When NOT to use:**
**Key patterns covered:**
**Detailed Resources:**
---
<philosophy>
Code review is about **improving code quality while teaching good patterns**. Every piece of feedback should help the author become a better developer. Be direct but constructive.
**When reviewing code:**
**When NOT to be harsh:**
**Core principles:**
</philosophy>
---
<patterns>
These checkpoints prevent review drift and ensure thorough analysis. Check yourself throughout the review process.
**Self-Correction Checkpoints:**
| Trigger | Correction | | ------------------------------------------------- | ------------------------------------------ | | Providing feedback without reading full file | Stop. Read the complete file first. | | Saying "this needs improvement" without specifics | Stop. Provide file:line references. | | Approving without checking success criteria | Stop. Verify each criterion with evidence. | | Focusing only on issues | Stop. Add positive feedback. | | Making assumptions about code behavior | Stop. Read the actual implementation. | | Flagging issues without explaining WHY | Stop. Add rationale for each issue. | | Reviewing code outside your domain | Stop. Defer to specialist reviewer. |
---
After completing your review, verify quality before finalizing.
**Reflection Questions:**
1. Did I read all relevant files completely before commenting? 2. Did I check against all success criteria in the spec? 3. Are my issues specific (file:line) and actionable? 4. Did I distinguish severity correctly (blocker vs improvement)? 5. Did I acknowledge what was done well? 6. Should any part go to a specialist reviewer? 7. Is my recommendation (approve/request changes) justified?
**Only finalize review when you can answer "yes" to all applicable questions.**
---
For multi-file reviews, track your progress to maintain orientation.
**Track These Elements:**
1. **Files Examined:** [list of files read completely] 2. **Success Criteria Status:** [checked/unchecked for each criterion] 3. **Issues Found:** [categorized by severity] 4. **Positive Patterns Noted:** [what was done well] 5. **Deferred Items:** [what needs specialist review]
For tracking examples, see [examples/core.md](examples/core.md).
---
All feedback should follow these principles for maximum effectiveness.
Every issue needs a precise location and actionable detail.
Don't just say what's wrong -- explain the impact so authors learn.
Point to existing patterns when possible.
Use clear markers to communicate priority:
| Marker | Category
The official skills marketplace for Agents Inc. 150+ skills covering everything from React and Prisma to Redis, ElevenLabs, and infrastructure tooling. Pick the skills that match your stack and install them via Claude Code. Need more control?
Repo: agents-inc/skills
Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation,…
LiteLLM proxy server setup, TypeScript client patterns via OpenAI SDK, model routing, fallbacks, load balancing, spend tracking, virtual keys, and production…
Serverless GPU compute platform for AI model deployment — web endpoints, GPU functions, model serving, and TypeScript client patterns
Local LLM inference with the Ollama JavaScript client -- chat, streaming, tool calling, vision, embeddings, structured output, model management, and…
Replicate SDK patterns for TypeScript/Node.js -- client setup, predictions, streaming, webhooks, file handling, model versioning, deployments, and training
Together AI SDK patterns for TypeScript — client setup, chat completions, streaming, structured output, function calling, embeddings, image generation,…