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Command Code

PaidAPISelf-HostedAgentic

Every other AI coding agent forgets your preferences the moment the session ends — and the next one opens with the same generic tab-vs-space fight, the same wrong package manager, the same patterns you've already corrected a dozen times. Command Code is built around that specific failure: it treats every accept, reject, and edit as a training signal, and converts those signals into persistent, shareable taste that follows you across sessions.

$1/mo · Checked Oct 22, 2026

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Summary

The agent runs in three modes — interactive CLI, headless with a prompt flag for scripted pipelines, and a background sandbox — so it fits scheduled jobs as well as live coding. Learned preferences compile into reusable skills automatically; no rules to write by hand. The team collaboration angle is real: one command pushes your taste profile, the whole team pulls it. Where the walls appear is less documented: open-model tool-calling support is a stated differentiator, but teams hitting complex multi-step agentic chains on open models will need to validate those claims against their specific stack before committing production workloads.

Bottom line: Bet this on a CLI-heavy solo or small-team workflow where preference drift and repeated corrections are bleeding velocity — pull back if your production pipeline depends on open models executing complex, multi-branch tool calls that the harness has not yet been stress-tested for.

Pricing Plans

SubscriptionLast verified 2 days ago
Price
$1/mo

Go

$1per month

From a buck a month to all-out, all-models. $10 in credits included. Up to ~$15 usage with deals.

  • ~9K requests
  • taste-1 model access
  • Per-model allowances: $10 on GLM-5.2, Tencent Hy3, Qwen 3.8 27B, Qwen 3.7 Max, Qwen 3.7 Plus, DeepSeek V4.1 Flash
  • Free access to Laguna S 2.1, Glyph Cluster, Beam 1.0, MiniMax M3.1 Flash, Ornith 1.5 122B
  • Limited usage analytics
  • Discord community support
  • No API access

GOAT

$10per month

Best value subscription in market. $80 in credits included. Up to ~$100 usage with deals.

  • ~75K requests
  • taste-1 model access
  • API access
  • Per-model allowances: $100 on Ling 3.1 Flash, $80 on DeepSeek V4.1 Flash, GLM-5.3 Flash, $70 on Tencent Hy3, Qwen 3.8 27B
  • Free access to Laguna S 2.1, Glyph Cluster, Beam 1.0, MiniMax M3.1 Flash, Ornith 1.5 122B
  • Usage analytics
  • Discord community support

Pro

$20per month

Pro plan with enhanced features.

  • ~100K requests
  • taste-1 model access
  • API access
  • Open-source + premium models
  • Usage analytics
  • Discord community support

Max 10u00d7

$100per month

Ship every day. Like magic. $150 in credits included. Up to $300 usage with deals.

  • ~219K requests
  • taste-1 model access
  • API access
  • Open-source + premium models
  • $300 on MiniMax M3
  • Up to 99% off MiMo V2.5
  • Free access to Laguna S 2.1, Glyph Cluster, Beam 1.0, MiniMax M3.1 Flash, Ornith 1.5 122B
  • Usage analytics
  • Higher rate limits
  • Priority support

Max 20u00d7

$200per month

All-out plan with maximum resources.

  • ~437K requests
  • taste-1 model access
  • API access
  • Open-source + premium models
  • Usage analytics
  • Higher rate limits
  • Priority support

Teams

$40per month

Better, together. Pooled usage. Shared billing. One bucket of credits for every member of the team.

  • ~35K requests
  • taste-1 model access
  • API access
  • Open-source + premium models
  • Team collaboration & management
  • Shared billing & central admin
  • Priority support

Enterprise

Custom

Tailored to your org. Custom credits & seats. Unlimited team seats.

  • Everything in Max
  • Custom credits & seats
  • Unlimited team seats
  • API access
  • Dedicated support engineer
  • SLA guarantees & uptime
  • Priority infrastructure
  • Custom training & onboarding

API Plan

$15per month

Pay as you go. No markup. Every deal, applied.

  • API: OpenAI and Anthropic compatible endpoints
  • Open-source + premium models
  • Per-request usage analytics
  • Discord community support
  • No fixed monthly commitment beyond $15

View full pricing on commandcode.ai →

Pricing may have changed since last verified. Check the official site for current plans.

Find your fit

Before you choose Command Code

More options in CLI Coding Agents. Compare pricing, platforms, and features side by side.

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Pros

  • Continuous preference learning from accepts, rejects, and edits — so you stop re-correcting the same patterns every session and the agent converges on your actual coding style over time.
  • Three distinct execution modes (interactive, headless, background sandbox), which means the same agent that assists during live coding can run unattended in a CI pipeline without a separate tool.
  • Persistent `/memory` and custom `/agents` scoped to a project, so context you built yesterday is available tomorrow without pasting it back into the prompt.
  • Team taste push/pull in a single command, so a lead's hard-won preference profile becomes the team's baseline instantly — replacing the undocumented tribal knowledge that causes style drift at scale.
  • Vendor-stated open-model harness support, so teams running DeepSeek or MiniMax can access tool-calling capabilities those models lack natively, reducing lock-in to closed-model providers.

Cons

  • The open-model tool-calling claim is the riskiest dependency: teams building multi-step agentic pipelines on open models have no published benchmark data to validate reliability under production load — only the vendor's stated architecture. Teams whose delivery timeline cannot absorb a harness failure mid-sprint will need to run their own stress tests before committing.
  • The learning loop requires an accumulation period — early sessions before enough accept/reject signal has been gathered will produce generic output indistinguishable from any other agent, which means teams evaluating it on a one-day trial will not see the core differentiation.
  • Complex branching agentic logic — tasks where the next step depends on what the previous step returned across four or more decision points — is not documented as a supported pattern. Teams with those requirements are more likely to move to an agent framework with explicit graph-based workflow control, at which point Command Code's taste layer becomes a side benefit rather than the primary system.

About

Platforms
CLI via npm
API Available
Yes
Self-Hosted
Yes
Last Updated
July 16, 2026

Best For

Who it's for

  • Developers wanting personalized AI coding assistance
  • CLI users seeking agentic workflows
  • Teams using open models in production coding

What it does well

  • Building and refactoring codebases with learned preferences
  • Running headless or background coding tasks
  • Collaborating via shared sessions and team taste pulls

Frequently Asked Questions

Is Command Code free?
Command Code is a paid tool ($1/mo). No permanent free tier is offered.
Does Command Code have an API?
Yes. Command Code exposes a developer API. See the official documentation at https://commandcode.ai for details.
Can I self-host Command Code?
Yes. Command Code supports self-hosting on your own infrastructure.
What platforms does Command Code support?
Command Code is available on: CLI via npm.

Most coding agents treat each session as a blank slate. Command Code’s core loop is different: it observes your accepts, rejections, and manual edits, then auto-generates what the vendor calls ‘project-level skills’ — reusable preference rules that carry forward without you writing a single config line. The CLI installs via npm, supports interactive, headless (`-p`), and `–yolo` modes, and ships with built-in file operations, shell access, grep, and extended thinking. Custom `/agents` and persistent `/memory` let you scope context to a project and carry it across every session.

The differentiation the vendor leans hardest on is the taste-1 model: a neuro-symbolic layer that pairs LLMs with your accumulated coding preferences. The explicit claim is that open models — which typically cannot tool-call reliably — work inside Command Code’s harness because the harness closes the gap. That’s a meaningful claim for teams trying to run DeepSeek or MiniMax in production without locking into a closed-model provider. The vendor also advertises significant discount pricing on those open models, which changes the cost math for high-volume coding tasks.

Command Code fits best in developer workflows where consistency of output matters more than raw generation speed — teams tired of correcting the same patterns across every new context window. The collaboration layer (`/share` sessions, `npx taste push/pull`) means a lead can codify team-wide conventions once and distribute them without documentation overhead. Where it is less proven: complex conditional agentic chains, large-scale background jobs with branching logic, and any scenario where open-model tool-calling reliability is the critical path. Teams in those situations will need to test against their actual workloads rather than take the stated benchmarks at face value.

Distribution is npm-global (`npm i -g command-code`). The system is described as hackable via `/skills`, `/commands`, `/mcp` servers, and plugins — meaning teams with specific conventions can extend the defaults without forking the core. A `/design` command covers interface audits and recoloring, which positions it for full-stack work beyond pure backend or CLI tasks.

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