Cog Review
- 5 installs
- 9.5k repo stars
- Updated August 4, 2026
- replicate/cog
Helps with ai & agent building tasks.
About
cog-review is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- cog-review
- AI & Agent Building
- AI-coding skill
Cog Review by the numbers
- 5 all-time installs (skills.sh)
- Ranked #13,065 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 5 |
|---|---|
| repo stars | ★ 9.5k |
| Last updated | August 4, 2026 |
| Repository | replicate/cog ↗ |
What it does
Helps with ai & agent building tasks.
Files
Cog architecture review guidelines
Cog packages ML models into production-ready containers. Use this skill for changes that cross language boundaries or touch core architecture.
Component overview
- CLI (Go):
cmd/cog/andpkg/-- builds, runs, and deploys models - Python SDK:
python/cog/-- predictor interface, types, HTTP/queue server - Coglet (Rust):
crates/-- prediction server inside containers (HTTP, worker management, IPC)
Key design patterns
Wheel resolution: The CLI discovers SDK and coglet wheels from dist/ at Docker build time. Wheels are NOT embedded in the binary. Changes to build artifacts need to account for this.
Dockerfile generation: pkg/dockerfile/ generates Dockerfiles from cog.yaml config. Template injection and escaping matter here.
Config parsing: pkg/config/config.go parses cog.yaml. Schema is at pkg/config/data/config_schema_v1.0.json. Changes must keep schema and Go code in sync.
Two-process coglet: Parent process (HTTP server + orchestrator) and child worker process (Python predictor execution) communicate via IPC. Changes to the IPC protocol affect both Rust and Python code.
Compatibility matrix: CUDA/PyTorch/TensorFlow compatibility is managed in tools/compatgen/. Framework version changes have wide blast radius.
Cross-cutting concerns
- VERSION.txt is the single source of truth for versioning.
Cargo.tomlmust match. - Changes to
python/cog/base_predictor.pyaffect all downstream model authors. - Changes to
docs/require runningmise run docs:llmto regeneratedocs/llms.txt. - CLI reference docs are auto-generated -- changes to
cmd/orpkg/cli/requiremise run docs:cli. - Integration tests in
integration-tests/use Go's testscript and need a built cog binary.
What to watch for
- Breaking changes to the predictor interface or cog.yaml schema
- Docker build changes that affect layer caching or build time
- IPC protocol changes without updating both Rust and Python sides
- Version bumps that miss one of the places VERSION.txt needs to match
- New ML framework versions without compatibility testing
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