Expert instructions for AI and infrastructure engineering
A library of instruction sets distilled from review discussions in production repositories — agent frameworks, inference servers, orchestration, databases, cloud infrastructure and the tooling around them. Each one is plain markdown: copy it here, or fetch it as raw text and load it into an agent, harness or context broker.
Domains
organized by engineering discipline
Agent loops, tool calling, prompt and context assembly, agent SDKs and coding assistants.
Inference servers, model gateways and routers, KV caching, retrieval and ingestion pipelines.
Training and inference frameworks, tensor and kernel code, ML platforms and pipelines.
Kubernetes, schedulers, service meshes, container tooling, workflow and job engines.
Infrastructure as code, cloud SDKs, edge runtimes, proxies, gateways and tunnels.
Query engines, storage, replication, streaming, ORMs and analytics backends.
Metrics, tracing, logging, error tracking and instrumentation of production systems.
Static analysis, cloud posture scanning, authentication, authorization and secrets handling.
Interpreters, compilers, async runtimes, parsers and low-level systems code.
Editors, terminals, build systems, package managers, linters, formatters and test runners.
Web and mobile frameworks, component libraries, API layers and product codebases.
Reference material, curated lists and learning resources — mostly writing and structure guidance.
Recently updated
Raw access
# one instruction
curl https://awesomereviewers.com/raw/pdf-inspector-evidence-gated-heuristics.md
# every instruction in a domain, concatenated
curl https://awesomereviewers.com/raw/bundles/ai-agents.md
# machine index: slugs, domains, dates, raw URLs
curl https://awesomereviewers.com/raw/index.jsonStable paths, no key, no rate limit. Regenerated on every push to the corpus.
Add a repository
Submit a public repository and it gets queued for extraction. Private repositories are handled through Baz.