WORK WITH AI
STRONGER
Production-grade Python CLI tools engineered for the next generation of AI-assisted development. Context, Agent, Quality — three layers, one ecosystem.
Three Layers. One Mission.
Codebase → AI context files (CLAUDE.md, llms.txt). 40+ languages.
Prompt template engine with token counting and cache annotations.
Intelligent context packing. Solves the #1 AI failure mode.
Bootstrap .ai/ + CLAUDE.md + AGENTS.md in one command.
Merge multiple project contexts for monorepo setups.
Natural language spec → structured task list (GitHub, Linear).
Semantic repo map with Mermaid diagrams and hub detection.
DuckDuckGo search + web scraping. AI-optimized content extraction.
Universal LLM adapter — Claude, OpenAI, Gemini, DeepSeek, one interface.
Task → cheapest adequate model. 50-80% cost savings on average.
Token usage + cost tracking across all providers with budget alerts.
Cross-session persistent memory for decisions, patterns, gotchas.
Terminal AI pair-programming. Full ecosystem integration, Aider-like.
Playwright + AI vision. Screenshot → UI/UX analysis in seconds.
Git diff → security + quality report. Can fail CI on critical issues.
Git diff → AI-friendly structured summary + auto-generated PR body.
Profiler output → bottleneck report. cProfile, py-spy, Lighthouse.
Raw logs → structured analysis with pattern matching and anomaly detection.
8-phase expert system for structured software development.
Git operations — clone, diff, log, remote read. All from CLI.
One Command.
Infinite Possibilities.
from ctxbuilder.scanner import scan
from smartpack.packer import pack
# Scan any project in milliseconds
info = scan("/path/to/project")
print(info.languages) # {"Python": 42, "TS": 15}
# Pack optimal context for AI
ctx = pack("fix auth bug", info,
budget_tokens=8000)
print(f"{len(ctx.files)} files")from apibridge import LLM
from smartroute.router import analyze
# One client, any provider
llm = LLM() # auto-detect from env
for chunk in llm.stream("Write tests"):
print(chunk.content, end="")
# Route to cheapest adequate model
route = analyze("Fix typo in README")
print(f"{route.model}: ${route.cost}")How We Compare
Honest comparison. We're not better at everything — we're different.
| Feature | CanAI | Cursor | Copilot | Aider |
|---|---|---|---|---|
| Multi-provider | ✓ 4+ (Claude, OpenAI, Gemini, DeepSeek) | ✗ Limited | ✗ OpenAI only | ✓ 4+ |
| Context packing | ✓ Smart file selection | ~ Basic | ✗ No | ✗ Manual |
| Cost optimization | ✓ Smart routing + tracking | ✗ No | ✗ No | ✗ No |
| Quality gate | ✓ Auto security + quality check | ✗ No | ✗ No | ✗ No |
| Zero dependencies | ✓ Stdlib only | ✗ N/A (IDE) | ✗ N/A (IDE) | ~ Some deps |
| Offline tools | ✓ Context + quality offline | ✗ Cloud only | ✗ Cloud only | ✓ With local models |
| Web UI | ✓ Chat + tools | ✓ IDE | ✓ IDE | ✗ Terminal only |
| Open source | ✓ MIT | ✗ Proprietary | ✗ Proprietary | ✓ Apache 2.0 |
| Price | Free (BYO API key) | $20/mo | $10/mo | Free |