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claudectl

#193 agent harnessverified Sep 4, 2026v0.64.0

6 MB Rust orchestrator for a swarm of Claude Code agents, backed by a local- LLM brain that learns from your own sessions

Key differences

6 MB Rust orchestrator for a swarm of Claude Code agents, backed by a local- LLM brain that learns from your own sessions

  • Runs local. Free and open source under MIT; you pay the model provider you configure
  • Runs local models. Listed for 65 of 194 tools in this category.
  • Runs multiple agents. Listed for 165 of 194 tools in this category.
  • Keep in mind: Code changes are made by the Claude Code agents claudectl orchestrates.

“Six megabytes and it starts in under fifty milliseconds, then waits nine seconds for a model to finish thinking.”

Website 201 starsCompare vs…Dispute a fact
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What it is

claudectl orchestrates a swarm of Claude Code agents from a single Rust binary of roughly 6 MB with sub-50ms startup and no required configuration. Its distinguishing piece is a local-LLM brain that learns from your sessions and shares knowledge across agents, and the CLI can report an impact scorecard of the numbers it has accumulated. It is published on crates.io and through the author's Homebrew tap.

Specification

Source verification

Row snapshot checked 2026-09-04. Individual checks below are recorded separately; automated release checks do not verify capabilities or pricing.

overview
Needs individual review
capabilities
Needs individual review
models
Needs individual review
license
Needs individual review
install
Needs individual review
website
Needs individual review

Architecture

Type
Agent harness
Runssrc ↗
local
Platforms
macos, linux
Context windowsrc ↗
not documented
Languages
any

Models

Backbonesrc ↗
Claude Code, local models
Bring your own model
Yes
Local models
Yes

Protocols

MCP clientunsourced
No
MCP server
No
OpenAPI tools
No

Capabilities

Terminal commandssrc ↗
Yes
Multi-file edits
Yes
Git operations
Yes
Browser control
No
Sandboxed execution
No
Multi-agent
Yes
Headless / CI
No

Cost

Modelunsourced
byok
Starts at
$0/mo
Free tier
Yes
Bring your own key
Yes

Free and open source under MIT; you pay the model provider you configure

Openness

Open sourcesrc ↗
Yes
License
MIT
First release
unknown
open-sourcerustharnessclaude-codeswarmlocal-models

Los Agentes on claudectl

Who are they?
The ruling
El JuezThe judge

El Profesor and El Hacker both stop at the same component and reach opposite conclusions about whether learning on your machine is a feature.

Trial only
Reasoning and trade-offs · AI analysis

El Hacker scores this well because the learning component runs on hardware he owns, so nothing leaves the room. El Profesor stops at the same component and asks who checked that the lessons are correct, since the tool grades its own contribution. El Crítico adds the part neither framed: nothing described here removes a lesson once it is wrong.

El Profesor wins, because a private mistake is still a mistake and it now propagates to every agent. El Hacker keeps the licence argument and loses the score. Trial only, and the exit criterion is a documented way to inspect and discard what it has learned.

Agree with El Juez?
El AmigoThe friend

Pick it if you already run several sessions at once and want them coordinated; pick a single agent if one window is still enough work for one day.

5.3
Reasoning and trade-offs · AI analysis

The deciding trait is that it demands nothing before it does something. No configuration file to write, no keys to lay out, no directory conventions to learn. You install it and it goes. For a category where setup regularly costs an afternoon, arriving with working defaults is a real courtesy and not a small one.

What you are buying, though, is coordination, and coordination only pays once you genuinely have several agents running. Pick it if you do. Pick a plain terminal agent if the honest answer is one at a time.

reliability
5
usefulness
5
cost
7
longevity
4
Agree with El Amigo?
El CríticoThe critic

A learning component absorbs your sessions and shares what it concludes across every agent, and nothing documented says how a wrong conclusion is removed.

4.8
Reasoning and trade-offs · AI analysis

Shared memory across agents is the failure mode nobody demos. Knowledge accumulated from past sessions is propagated to the whole swarm, so a pattern learned from one bad afternoon becomes the default assumption everywhere, and the row records no expiry, no confidence threshold and no command that forgets. Debugging then means debugging a history you cannot read.

What it does right is running without configuration, which at least means the surface you have to reason about starts small.

reliability
4
usefulness
5
cost
6
longevity
4
Agree with El Crítico?
El ProfesorThe professor

The impact scorecard is produced by the tool measuring itself, using numbers it accumulated, with no stated method and no external comparison.

4.5
Reasoning and trade-offs · AI analysis
  1. Self-measurement is not evidence. A command that reports the value a tool has delivered, computed from figures that same tool recorded, has no control condition and no independent observer, and the row gives no methodology to inspect. 2. This is a category error rather than dishonesty: the quantity being reported is activity, and it is presented as impact.

  2. A defensible version would state what was counted, against what baseline, and over which period. Until then the scorecard belongs in the interface, not in an argument.

reliability
4
usefulness
4
cost
6
longevity
4
Agree with El Profesor?
La InversoraThe investor

197 stars, a solo author publishing through a package registry and a personal tap, and no company anywhere in the picture to fund a second year.

4.5
Reasoning and trade-offs · AI analysis

Distribution here is the author's own channels, which is fine for reach and tells you there is no organisation behind the release. Under two hundred stars is a signal of curiosity from other developers rather than dependence by teams, and there is nothing to sell, nothing to price, and no entity that could be bought.

Moat: none, and orchestration is the layer platform vendors reclaim first. Likely acquirer: no transaction happens; the author gets a job. Position: pass, unless the coordination problem is already costing you real hours.

reliability
4
usefulness
4
cost
7
longevity
3
Agree with La Inversora?
La JefaThe CTO

Free across sixty desks and sixty provider subscriptions underneath it, with nothing that runs unattended and no administrative surface of any kind.

3.8
Reasoning and trade-offs · AI analysis

The real bill is not this. It is the underlying agent subscriptions multiplied by the number of engineers who would use it, and that figure is the one my finance director will read aloud. What comes back for it is a desktop convenience with no console, no single sign-on, no directory sync and no retention statement.

It does not execute unattended, so nothing it does becomes a pipeline step, a gate, or a metric I can put in a board pack. Onboarding is quick, which is the only line in its favour. Not yet.

reliability
3
usefulness
4
cost
5
longevity
3
Agree with La Jefa?
El HackerThe tinkerer

MIT, one static Rust binary I can drop anywhere, and local weights are a supported destination rather than a footnote about future work.

6.8
Reasoning and trade-offs · AI analysis

A permissive licence and a self-contained binary is the deployment story I want: copy it onto a box, run it, no runtime to install first and no package manager arguing with another package manager. The fork stays viable and the source is short enough that fixing something myself is a realistic afternoon rather than a fantasy.

Local inference being supported matters more here than anywhere else on this board, because the component that watches my work is then watching it on my hardware. What I cannot do is attach the servers I already run.

reliability
7
usefulness
6
cost
8
longevity
6
Agree with El Hacker?