CodexLoom Agent Organization

Turn Codex threads into a governed team of agents with durable domain responsibilities.

Source repo
yan5xu/codexloom
Stars
★ 387
Last updated
1mo ago
License
NOASSERTION
Primary language
Go

At a glance

How it runs
Self-hosted serviceWeb appCLI
Works with
Platform-specificChatGPT · Codex (Partial support)
Setup effort
Medium · a few setup steps
You'll need
Codex CLIChatGPT accountShell / CLINetwork accessLocal filesystem
Typical use
A solo developer wants Agents to own projects, subsystems, or professional domains over time and continue from existing thread context.
Not a fit if
  • Organizations that need enterprise multi-tenant administration
  • Teams seeking a runtime other than Codex

What does this agent do, and when should you use it?

CodexLoom is a local-first, self-hosted environment built on Codex that organizes continuing Codex threads as long-lived Domain Agents. Each Agent has a stable ID, name, Profile, and primary Thread, and can resume work through Codex Desktop, Mobile, the WebUI, or CLI. Agents coordinate through Messages, Topics, and managed Artifacts, while an Owner governs their relationships, authorization, and external Conversation Memberships. The project starts with the Codex CLI and a ChatGPT account, and is operated through its WebUI and `loom` CLI; external collaborators can participate through Feishu, Slack, or Parall. It is aimed first at an advanced individual Owner managing an Agent team, rather than enterprise multi-tenant administration.

The Owner runs make release to build the project, starts ./bin/codex-loom, and uses the local WebUI to create Agents, assign working directories, send work, and write Profiles. Each Agent's primary Thread carries ongoing tasks, tool calls, decisions, and feedback; CodexLoom maintains its identity, Team relationships, status, and runtime evidence. Agents can use the loom CLI to discover domain owners, send or reply to Messages, inspect delivery state, and coordinate bounded work through Topics; final files can be handed off as managed Artifacts. The Owner can inspect Organization, Collaboration, and Activity maps, Schedules, Triggers, and runtime state, and configure external identities and Conversation Memberships. With authorization, an Interface Agent can route an external conversation request to the responsible Domain Agent and return the result to that conversation.

  1. A solo developer wants Agents to own projects, subsystems, or professional domains over time and continue from existing thread context.
  2. An Agent team needs to ask domain owners questions and coordinate follow-up through Messages and Topics.
  3. An Owner wants to bring established domain capability into existing Feishu or Slack conversations while governing membership and disclosure.
  4. An Agent maintainer needs to review daily activity, capacity, and runtime state before manually changing responsibilities or relationships.
  5. A small team needs managed Artifact handoffs for final files produced by cross-Agent work.

How do you install or deploy this agent?

The documented source startup requires the Codex CLI and signing in with a ChatGPT account. In the repository, run:

make release
./bin/codex-loom

Then open http://localhost:4870 for the WebUI. The README does not specify other required system dependencies or versions for the build.

How do you use this agent?

In the WebUI, select New agent, enter a stable name and working directory, open the workspace, and send a real assignment. Use Profile in the Agent Inspector to record Identity, Domain, and Scope. The initial setup can also be done with the local CLI:

./bin/loom agent create research --cwd /path/to/repo
./bin/loom profile set research \
  --identity "Long-term researcher for this domain" \
  --domain "Continuously research the relevant products, protocols, and implementations" \
  --scope "Answer domain questions, preserve conclusions, and advise related agents"
./bin/loom thread send research "Establish a baseline for the current state of this domain"

Continue the same primary Thread from Codex Desktop, Mobile, WebUI, or CLI. Use the loom CLI messaging commands for cross-Agent collaboration.

What are this agent's strengths and limitations?

Pros
  • Keeps a continuing Codex thread as a long-term domain workspace, carrying forward context and work history across tasks.
  • Defines durable Agent identity, Profile, and collaboration boundaries, with Messages, Topics, and Artifacts for distinct coordination and handoff needs.
  • Makes the same Agent available through Codex Desktop, Mobile, WebUI, and CLI, with external conversation integrations for Feishu, Slack, and Parall.
  • Separates formal responsibility, declared collaboration, and message activity across Organization, Collaboration, and Activity maps.
Limitations
  • Depends on the Codex runtime, Codex CLI, and a ChatGPT account; it is not a standalone model runtime.
  • The project is under active development, and Remote depends on experimental Codex APIs that may change across releases.
  • It primarily serves one advanced individual Owner; enterprise multi-tenant administration and general company operations are not its focus.
  • Patterns such as Lead and Internal Agent are expressed through Profiles and relationships; hierarchical messaging policies and organization templates are still being modeled.

How does this agent compare with similar options?

The README contrasts CodexLoom with task-oriented agent workflows: it organizes around continuing domain responsibility and accumulated thread context instead of starting a new thread for each task. It does not name another directly comparable product.

Key facts side by side with the most closely related agents.

Agent Source review Form / cost Stars Updated Language Full support on
CodexLoom Agent Organization This agent 51 · Major gaps Self-hosted service ★ 387 1mo ago Go —
OpenRig 79 · Good CLIFree + model costs ★ 6.4k today TypeScript Codex · Claude Code
Maestro Orchestration Platform 75 · Some gaps Agent plugin / skillFree + model costs ★ 465 5mo ago JavaScript Codex · Claude Code
MCO 73 · Some gaps CLIFree + model costs ★ 531 2d ago Python Codex · Claude Code

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
51/ 100 5-point scale 2.6 / 5
Trust 11/29
Reliability 6/14
Adaptability 12/18
Convention 11/18
Effectiveness 7/13
Verifiability 4/8
Why each dimension lost points
Trust11 / 29 · 1.9/5

The README describes conversation memberships, authorization and information boundaries, external identities, inbox/outbox, and human authorization. The supplied material does not show permission enforcement, sensitive-data protections, or confirmation flows for external actions, so those areas receive only partial credit. go.mod lists a keyring dependency but does not explain its coverage or dependency-security practices. On-demand backups are mentioned without a restore or rollback procedure. The project says it is independent and not endorsed by OpenAI, but publisher identity is unverified and maintenance and update responsibility are unclear.

Reliability6 / 14 · 2.1/5

The README gives a coherent account of long-lived agents, threads, profiles, collaboration, and external interfaces, and acknowledges that some hierarchical messaging policies are still being modeled. It depends on the Codex CLI and experimental Codex APIs; the documentation says interfaces and backend behavior can change between releases, so dependency availability scores low. The supplied files give little detail about specific failure messages or recovery behavior, earning only partial credit.

Adaptability12 / 18 · 3.3/5

The material identifies advanced individuals and one-person company owners as the primary audience and says enterprise multi-tenant administration is not the current product direction. It gives concrete boundaries for Agents, Interface Agents, Conversation Memberships, and organizational relationships, so capability boundaries receive full marks. Triggers appear in a feature list and documentation links, but their conditions and scenarios are sparsely described. The local-first, self-hosted model and Codex CLI requirement are stated, while platform compatibility and deployment requirements remain incomplete.

Convention11 / 18 · 3.1/5

The README organizes product concepts, quick start, governance, and documentation links, with a documentation map and several topic guides. Quick-start commands, a WebUI address, and a CLI example are provided, but complete dependency installation and troubleshooting instructions are not. Terms and roles are defined, with examples and known limitations. No changelog or versioning policy is included in the supplied files. The ELv2 text and the source-available, non-OSI-open-source status are clear; maintenance responsibility and the update path are not.

Effectiveness7 / 13 · 2.7/5

The product describes understandable outputs, including long-lived threads, durable profiles, agent messaging, managed handoffs, and external collaboration, and provides a starter workflow for one Agent. Its claimed relative value rests mainly on reducing repeated context and organizing ongoing responsibility, without outcome or cost evidence. The costs of operating Codex, maintaining long-lived context, and configuring external platforms are not quantified, keeping these scores moderate or low.

Verifiability4 / 8 · 2.5/5

The README links many claims to topic documents and distinguishes organizational relationships, message evidence, and performance judgments; it also labels some feature status and experimental dependencies. The supplied evidence is mostly the README, license, Go dependency manifest, and test setup file. Implementation code, a changelog, or independent corroboration is absent for many product capabilities. The documentation separates some product statements from stated limitations, but many capabilities remain assertions rather than implementation evidence in the supplied files.

Risks and how to mitigate them
  • This assessment uses only the files supplied in the prompt; many product capabilities are described in the README without implementation code to corroborate them.
  • The project depends on the Codex CLI and experimental Codex APIs, whose compatibility may change across Codex releases.
  • Before using external platforms, verify the actual authorization, data disclosure, sensitive-data protection, and recovery flows; the supplied material does not fully document these implementation details.
Evidence confidence: Low Reviewed Oct 09, 2026 Reviewed revision 332d4a853719
See the full review method →

FAQ

Does CodexLoom replace Codex or keep a separate copy of thread history?
No. Codex supplies the Agent runtime and thread history; CodexLoom adds durable identity, Profiles, Team relationships, coordination, and governance on top.
Do Agents enter one another's primary Threads?
No. They coordinate through bounded Messages, Topics, and managed Artifact handoffs; they do not resume another Agent's primary Thread.
Can external group members access internal Agents, threads, or credentials?
External Conversation Membership does not grant direct access to those resources or decision authority. Internal routing and disclosure are subject to explicit authorization and information boundaries.
Does using CodexLoom cost money?
The README does not state software pricing or the cost of Codex and ChatGPT accounts, so the total cost cannot be determined from it.
Which external conversation platforms are available?
The README lists Feishu (Lark), Slack, and Parall as available. Microsoft Teams is marked TODO.
View on GitHub ↗ Install ↓

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