# optimize `codeburn optimize` scans your Claude Code sessions and your `~/.claude/` setup, reports what is costing tokens without earning them, and grades the setup A to F. ## What it scans - **Session transcripts** for the selected period: tool calls, per-call token usage, turn retries, per-session cost, and the block each session opens with. This is where re-reads, junk directory reads, low read:edit ratios, warmup overhead, retries, context pasted into session after session, and expensive or context-heavy sessions come from. - **Your configuration**: `~/.claude.json`, user and project `settings.json` / `settings.local.json`, `.mcp.json`, `CLAUDE.md` (including `@`-imports), and the `skills/`, `agents/`, `commands/` directories. This is where unused MCP servers, MCP deferral gaps, ghost skills/agents/commands, the bash output cap, and oversized `CLAUDE.md` files come from. Nothing is written during a scan. Only `--apply` writes. ## The three classes Every finding carries a `class`, and both the CLI and the apps group by it: | Class | Header | Meaning | |---|---|---| | `fix` | Fix now (apply-able) | CodeBurn can make this change for you: `codeburn optimize --apply` | | `nudge` | Habits | Behavioural. Nothing to edit; the fix is how you drive the next session | | `keep` | FYI | Informational. The cost may well be justified; decide for yourself | A finding is `fix` only when a plan can actually be built for that instance. The same detector can report a `fix` in one run and a `nudge` in another: `mcp-deferral-off` is appliable when the cause is an `ENABLE_TOOL_SEARCH` override in a settings file, but manual when the cause is Vertex AI policy, an outdated Claude Code, or an override that lives in your shell profile. ## What `--apply` may write `--apply` builds a plan per finding, shows you the exact files it will touch, and asks before writing. `--dry-run` prints the plan and stops. | Finding | File it edits | |---|---| | `unused-mcp`, `mcp-low-coverage` | `~/.claude.json`, project `.mcp.json` / `settings.json` (removes the server entry) | | `mcp-project-scope` | moves a global server entry into the keeper project's `.mcp.json` | | `mcp-deferral-off` | the settings file carrying the `ENABLE_TOOL_SEARCH` override | | `mcp-alwaysload-hygiene` | the config files carrying `"alwaysLoad": true` | | `mcp-defer-threshold` | the settings file carrying the `auto:N` threshold | | `unused-agents`, `unused-skills`, `unused-commands` | moves the files into `~/.claude//.archived/` | | `bash-output-cap` | appends a marker block to `~/.zshrc` / `~/.bashrc` | | `read-edit-ratio`, `build-folder-reads` | appends a marker block to the current project's `CLAUDE.md` | Every write is backed up and journaled first: ```bash codeburn act list # every change CodeBurn has made codeburn act undo # restore the original files codeburn act undo --last ``` Undo refuses if a file changed after the apply, unless you pass `--force`. ### The `--yes` CLAUDE.md guardrail `--apply --yes` skips the prompt for every plan except `CLAUDE.md` rule blocks. Those land in the `CLAUDE.md` of whatever directory you happen to be in, so a blanket `--yes` from an unrelated directory would write advice into the wrong project. To apply one anyway, use the interactive picker or name it explicitly: ```bash codeburn optimize --apply --only read-edit-ratio ``` ## After you apply Applying a fix is a claim, so CodeBurn checks it. Every `codeburn optimize` run re-measures the fixes still in place and prints them under `Applied fixes`, one line each: | Line | Verdict | Meaning | |---|---|---| | `✓ unused-skills (7d ago): est. 300.0K -> measured 280.0K` | worked | at least 70% of the estimate showed up in your sessions | | `~ mcp-defer-threshold (5d ago): est. 600.0K -> measured 420.0K (-30% vs estimate)` | partial | it helped, but under its estimate | | `✗ bash-output-cap (6d ago): est. 41.0K -> measured 0 - did not help. Revert: codeburn act undo 3f2a1c04` | no-effect | no measured reduction at all | | `… mcp-remove (1d ago): measuring, check back after 3 days` | measuring | too young, or the change has not taken effect in a session yet | The estimate shown is the at-apply estimate scaled to the measured window, so the two numbers are comparable. Both come from the same reconciliation `codeburn act report` prints — there is one set of numbers, not two — and they are **measured**: provider-counted usage over the post-apply window. Anything that cannot be measured (no baseline captured, a fix you reverted by hand, a correlation-only kind like `guard-install`) stays on the `measuring` line with the reason, never a claimed saving. `--format json` carries the same list as `appliedFixes[]`, and the section appears in the dashboard TUI and the desktop app. ### `--auto-revert` ```bash codeburn optimize --auto-revert ``` Off by default. It undoes exactly the fixes whose verdict is `no-effect`, through the same code path as `codeburn act undo` (backups restored, drift check applied, the revert journaled). It never touches a `partial` or still-measuring fix, and it never auto-reverts a `claude-md-rule` — those land in whatever project directory you were in, the same reason `--yes` skips them, so it prints the undo command and leaves the file alone. ## measured vs estimated Each finding also carries a `basis`, printed next to its savings and summarised in the header as `N measured · M estimated`: - **measured** — the token number is summed from provider-counted usage on your own calls. Today that is `context-heavy-sessions` and `cost-outliers`. - **estimated** — the token number comes from a model: a per-tool schema size, a per-line `CLAUDE.md` cost, an average read size, a recovery fraction applied to real turn tokens. A detector that mixes counted tokens with a model counts as estimated. Sessions whose cost the provider never reported (Kiro, Cursor, some Cline sessions price from modelled token counts) are kept out of the `cost-outliers` peer comparison, so a modelled cost is never called an outlier against provider-reported ones. When a provider only ever estimates, the comparison falls back to those sessions and the finding reports itself as `estimated`. In `--format json`, `summary.measuredSavingsUSD` is the share of `summary.potentialSavingsCostUSD` that comes from measured findings. ## Reading the health grade Health starts at 100 and loses points per finding: 15 for a high-impact one, 7 for medium, 3 for low. The total penalty is capped at 80, so a long tail of small findings cannot sink the score to zero on its own. The grade is a band over that score: | Grade | Score | |---|---| | A | 90-100 | | B | 75-89 | | C | 55-74 | | D | 30-54 | | F | below 30 | The grade rates your setup, not your spending: an expensive month with a clean configuration still scores an A.