Expose usage + model controls for -p (non-interactive) automation

Context

We're hitting Command Code from an automated multi-agent orchestrator that fans out coding tasks across several CLI agents (codex CLI, Claude Code, Command Code). The orchestrator picks an adapter per task and records token usage + cost + model for budgeting, audit, and savings telemetry (subscription vs. metered API).

Command Code is in the consideration as the open-weights path. We invoke it via commandcode -p <prompt> --skip-onboarding --yolo -t inside a per-task working directory, which works great — the agent runs, edits files, returns clean stdout. But three control surfaces that exist on codex exec and claude -p are missing on commandcode -p, which forces us to flag those dimensions as "unknown" on every run.

Filing one bundled ask because the three are tightly related (programmatic control of a non-interactive run).

Asks

1. Emit usage in -p output (highest impact for us)

claude -p --output-format json returns:

{
  "type": "result",
  "total_cost_usd": 0.1969,
  "usage": {
    "input_tokens": 4,
    "output_tokens": 8,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0
  },
  "num_turns": 1
}

codex exec persists similar info to ~/.codex/sessions/<date>/rollout-*.jsonl (event_msg records with type: 'token_count').

What we'd love from commandcode — either of these works:

• (preferred) commandcode -p --output-format json <prompt> that returns a final JSON line with at minimum { tokens: { input, output, cached? }, model, provider, plan_type? }.
• (alt) Persist usage in the session JSONL at ~/.commandcode/projects/<slug>/<sessionId>.jsonl so we can post-hoc read it the same way we read codex rollouts. Today the JSONL records role / content / timestamp / parentId / gitBranch / metadata.{source,version,messageId} — no usage/tokens/cost field anywhere across the captured sessions we've inspected.

A surprise we hit: -p --skip-onboarding --yolo -t mode doesn't seem to create a project dir entry at all for our system-tmp-rooted working directories (every other commandcode mode does). If usage lands in the project JSONL we'd also want -p mode to create it.

2. --model <id> flag on commandcode / commandcode -p

codex exec --model gpt-5-codex and claude -p --model sonnet accept a per-invocation model pin. Today the only way to switch Command Code's active model is the interactive /model slash command (or Alt+P quick switch), which is unreachable from -p.

Ask: accept --model <id> on the top-level CLI (and on -p), overriding ~/.commandcode/config.json's model field for the duration of the invocation. A COMMANDCODE_MODEL env var would also work and is arguably easier to wrap.

Use case: an orchestrator that picks the model per task can't currently pin commandcode the way it pins the other CLIs — it has to silently fall back to whatever the operator last selected via /model, which makes the open-weights lane the only one without per-task model control.

3. commandcode status --json (small but useful)

The interactive /context slash command shows context window usage. Surfacing status --json with { user, model, provider, plan_type, context_window, auth: 'oauth'|'api-key' } would let automation:

• detect the active model + plan without parsing TTY output
• record auth mode in session events so it can compute "saved vs. theoretical" cost (we do this for claude via JSON output: actual=0 / theoretical=0.1969 when running on subscription)

What we're shipping in the meantime

To be transparent about the workaround: our adapter currently emits a loud budget.unsupported-dimension skip log on every commandcode run for tokens, usd, tool-calls, and (when set) a per-task model override. We treat the open-weights run as untracked — better than silently fabricating an estimate. Tiktoken-based estimation is a fallback we'd rather avoid since GLM tokenization isn't byte-identical to GPT/Claude tokenizers.

CLI versions tested

• commandcode 0.25.13
• claude --version and codex --version for shape comparison
• macOS Tahoe 26.4.1 (darwin/arm64), Node 25.9.0

Happy to chat / file three separate issues

If you'd prefer three separate issues (-p --output-format json, --model flag, status --json) just say the word. Bundling here for context because they all serve the same automation use case.

Thanks for shipping Command Code — the /init AGENTS.md auto-load and the open-weights option are exactly what we needed for an automated open-weights lane.