Quota and models

Then review my Claude Code setup against it: my user and project settings, the subagents in ~/.claude/agents and .claude/agents, CLAUDE.md, and the MCP servers I have connected. Find three kinds of problems:
1. A default effort that doesn't fit the work. Use the guide's ladder: low for mechanical edits, medium for well-scoped daily work, high when medium stalls, and xhigh or max only for work where a gain was measured. Flag a default of xhigh or max, or a level I picked for Op…

CLAUDE_CODE_SUBAGENT_MODEL=opus
model: opus
effort: medium

Set up my Codex to match this tree:
→ Main session: default to `gpt-6.1-sol` on high reasoning effort. It breaks down tasks, delegates, integrates, and verifies. Handle simple tasks directly; don't delegate them.
→ Three project-level custom agents, each with model `gpt-6.1-sol` and model_reasoning_effort `medium`: explorer reads code, worker edits code and runs tests, researcher looks up docs.…

Read this doc, plus the status line field reference it links to, and add a cache segment to my Claude Code status line.
1. If I already have a status line, don't replace it. Save stdin first so the original command and the cache segment read the same input, leave the original output as is, and put the cache segment on its own line after it. If I don't have one, create one.
2. Get the data from prompt_cache in the input: warm, ttl, expires_at, hit_ratio, misses, last_miss_cause…

Then list every place in this project that calls the Claude API, estimate which one costs the most, and let me pick one. Use build-eval from the claude-api skill to build a test set for it, and tell me roughly what it will cost in API fees before you run anything.
Once I've approved the test cases and the grading, run hillclimb on a new branch. The goal is to keep accuracy and cut cost. You can try lower effort and cheaper models, including Sonnet 5.5. The report should spell…