KevinZai Large Context
What This Does
Handles work whose input is too big to reason about in one pass — whole codebases, large document sets, long transcripts.
This replaced gemini-fallback in v7.3.2. That skill existed to escape "Claude's 200K limit" by routing to a third-party 1M-context model. Both halves of that premise are gone: Claude Opus 5 has a 1M-token context window by default (it is the default and the maximum — no [1m] suffix needed), and CC Commander routes to Anthropic models and the Codex CLI only. There is no Gemini path and no local-LLM path.
Instructions
Work down this ladder. Stop at the first rung that fits — each costs more than the one above it.
1. Just use the window (default)
Opus 5 gives you 1M tokens. Most "too big" tasks are not actually too big anymore. Measure before engineering around it:
# rough estimate — chars/4 is close enough to decide
find <path> -type f -name '*.ts' -exec cat {} + | wc -c | awk '{print int($1/4)" est. tokens"}'
Under ~800K estimated tokens: read it directly. Don't build a pipeline for a problem you don't have.
2. Reduce before you chunk
If it genuinely exceeds the window, shrink the input before splitting it:
- Filter to the files that matter (
rg -l '<symbol>'beats reading the tree). - Strip generated output, lockfiles,
node_modules, build artifacts, vendored code. - Summarize per-file, then reason over the summaries.
A 3M-token repo is usually a 200K-token repo plus noise.
3. Chunk and synthesize
Still too big — split on a natural boundary (module, chapter, date range), process each chunk in its own subagent, and have each return conclusions only, never raw content. Synthesize the returned findings in the lead context.
Per the Opus 5 delegation rules: fan out only when chunks are genuinely independent, and keep spawn counts low. Three sequential passes beat thirty parallel agents returning file dumps.
4. Hand execution to the Codex CLI
When the job is mechanical over a large surface (repo-wide rename, codemod, bulk migration), plan with Claude and let the Codex CLI execute against the plan:
codex exec -m gpt-5.6-sol -c reasoning_effort=high "$(cat plan.md)" < /dev/null
Codex runs read-only by default; pass -s workspace-write to let it write, and only inside an isolated git worktree on its own branch. Review the diff before merging — the same gate any subagent's work gets.
Guardrails
- Never route to a local LLM or a third-party model. Anthropic + Codex CLI only. This is a deliberate product constraint, not an oversight — it keeps behaviour predictable and every documented workflow reproducible on a stock install.
- Chunk boundaries must be semantic. Splitting mid-function or mid-argument produces confidently wrong summaries.
- Subagents return conclusions, not content. Pulling raw chunks back into the lead context re-creates the problem you were solving.
- State the reduction. If you filtered 3M tokens down to 200K, say what you dropped — a synthesis over a silently truncated corpus reads as complete when it isn't.
Related
ccc-research/deep-research— multi-source research synthesisccc-research/cross-model-review— second-opinion review via the Codex CLI/ccc-orchestrate— plan on Claude, execute on Codex, verify on Claude