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Before dispatching a single token to Claude Code, CC Commander runs four analysis modules that together decide the right model, budget, turn limit, and skills for your task. You never touch a config flag — the Intelligence Layer handles every dispatch automatically based on what your task actually needs.
The Intelligence Layer runs automatically — no configuration required.

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The four modules

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1. Weighted complexity scoring

Every task you describe is scored from 0 to 100 using 47 keyword signals, word count, and fuzzy regex matching. The score maps directly to a model, turn limit, and dollar budget.
The scorer starts at a baseline of 30 and adjusts up or down based on what it finds in your task description: The four score ranges and what they produce: File scope estimation adds a 0–20 point bonus by scanning how many project files the task is likely to touch. You never need to set --model, --budget, or --max-turns manually.

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2. Stack detection

Before every dispatch, CCC reads your project directory and detects your technology stack automatically. It parses package.json, Dockerfile, go.mod, and requirements.txt. It also reads your current git branch and the themes of your last five commits, and detects monorepo setups (workspaces, lerna, turbo, nx). From those files it recognizes: nextjs, react, vue, docker, python, rust, go, github-actions, orm, billing, and testing frameworks. No configuration needed — CCC reads what is already in your project.

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3. Skill recommendations

Once the stack and task are known, CCC’s skill recommender combines three signals to surface the most relevant skills: Trending skills (7-day window) surface automatically. Skills that led to successful sessions compound their ranking advantage the more you use them.

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4. Knowledge compounding

Every completed session extracts a lesson — keywords, category, tech stack, error patterns, success patterns — and stores it in ~/.claude/commander/knowledge/. The next time you dispatch a similar task, those lessons are injected into the session prompt automatically. Relevance is weighted by time: Fuzzy keyword matching and cross-domain boosts (web↔react, api↔backend, testing↔bugfix) catch related concepts across categories. Outcome weighting gives successful sessions a 1.5× boost and error sessions a 1.2× boost, so the knowledge base gets more useful the more you build.

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Smart dispatch in action

Here is what CCC’s analysis output looks like before a session starts:

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How it compounds over sessions

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Smart retry

The Intelligence Layer also handles failures automatically so you do not need to babysit long sessions:
  • Rate limit hit — waits 60 seconds, then retries automatically
  • Context overflow — reduces turns to 60% of original, then retries
  • Budget exceeded — surfaces a clear error with next steps
You can view your accumulated knowledge base stats at any time by running ccc --stats.