CLIO Command Line Intelligence Orchestrator
A terminal-native coding agent that investigates repositories, edits files, runs tests, and works through development tasks with you.
Per-dimension scores and reasoning
The evidence describes authorization for paths outside the project, confirmation for high-risk commands, tool enable/disable controls, sandbox and container isolation, undo, local credential/session handling, and transmission of context to AI providers. This adequately supports ordinary-use privilege, confirmation, external-effect, rollback, and data-flow controls. Deductions apply because in-project operations are auto-approved, the default redaction level covers only PII, API keys are stored in plaintext JSON, certificate-validation details vary by provider, and no vulnerability scanning or commit-pinned supply-chain controls are shown. The author, organization, license, and support paths are attributed, but publisher identity is unverified and the security contact is only indirectly identified through a profile.
The README, test scripts, and release workflow consistently cover sessions, file operations, errors, dependency checks, and version validation, with reasonably specific failure messages. Deductions apply because release CI explicitly skips tests requiring API keys; the syntax-check loop changes FAILED inside a pipeline subshell and may not propagate module failures; and “zero dependencies” means no CPAN/npm/pip packages rather than no dependencies, since Perl, git, curl, and Unix tools remain required. Static evidence cannot establish runtime reliability.
Terminal developers, SSH, multiplexers, Docker, headless systems, local and remote work, multiple providers, and multi-agent scenarios are described thoroughly, while platform requirements and startup modes are clear. Capability boundaries include OS and Perl requirements, sandbox restrictions, and security limitations, but many broad capabilities remain assertions. Risk classification, path authorization, and tool allow/deny switches support reasonably precise triggering, although implementation evidence needed to assess classification accuracy and edge cases is absent.
The README has strong organization across features, commands, providers, installation, security, documentation, and support. Installation alternatives and examples are substantial, and CLIO naming plus date-based version examples are stable. Known security limitations are unusually explicit. Deductions apply because there is no actual FAQ and linked detailed documents were not supplied; metadata says GPL-3.0 while the README says GPL-3.0-or-later, and the supplied generic GPLv3 text does not resolve that qualifier. Releases generate notes and validate versions, but no historical changelog is supplied and the workflow may modify and push a version file. A maintainer and support paths are named, though no direct security email is given and only the latest release is supported.
The terminal interface, persistent sessions, approval-based planning, file and Git tools, undo, usage reporting, and provider choice form a plausibly useful development workflow with actionable outputs. Deductions apply because benefits are predominantly README claims, the supplied end-to-end scripts require live providers and are skipped in release CI, and no output corpus, comparative quality evidence, or cost benchmark is supplied. Core-only Perl dependencies and local operation reduce setup cost, but model fees, token consumption, remote-orchestration cost, and maintenance overhead are not quantified.
Claims are traceable to named documents, modules, commands, tests, and release automation. Security statements receive some corroboration between README and SECURITY.md, while versioning statements are partly corroborated by workflows. Deductions apply because central implementation files and linked documents are absent, no test results are supplied, and full tests are deliberately omitted from release CI. Promotional statements such as code staying local, defense in depth, and self-development are not clearly separated into verified facts, design intentions, and inference.
- The default redaction level is pii and, according to the supplied table, does not redact API keys or tokens. Switch to standard or strict and verify configuration-file permissions before using sensitive repositories.
- CLIO can edit files, execute commands, and perform git push/pull operations; actions inside the project are auto-approved. Begin in a container or --sandbox and inspect plans and diffs before external effects.
- API keys are stored unencrypted in ~/.clio/config.json, and certificate-validation details vary by provider. Keep configuration and session directories out of repositories and connect only to trusted endpoints.
- Release CI skips tests requiring API keys, and the syntax-check pipeline may lose module failures through subshell scoping. A green release workflow should not be treated as proof of a complete test pass.
- The Docker example uses the mutable latest tag, while GitHub Actions are pinned only to major-version tags. Higher-assurance deployments should pin image digests and action commit hashes and perform separate dependency and image scanning.
- The GPL-3.0 versus GPL-3.0-or-later wording is inconsistent. Confirm the intended licensing scope with the maintainer before redistribution or integration.
What does this agent do, and when should you use it?
CLIO is a terminal-native AI coding tool for developers who work in local shells, SSH sessions, tmux, Docker, or headless servers. It reads and searches project files, executes commands, edits code, and performs Git operations including diffs, commits, branches, pushes, pulls, stashes, tags, and worktrees. Its normal workflow is to investigate the repository, propose a plan, wait for approval, and then implement, test, and optionally commit the changes. The program is written in pure Perl using core modules, while its operating environment requires Perl 5.32+, Git, curl, standard Unix tools, and either macOS 10.14+ or modern Linux. Persistent sessions, cross-project memory, a working-style profile, coordinated sub-agents, Git-loaded skills, plugins, and MCP servers form its collaboration and extension layers; work can remain on the local project, run inside Docker, or execute on another machine through SSH.
After receiving a task, CLIO examines the codebase, prepares a plan for approval, and then reads, writes, searches, and edits files, executes commands or scripts, runs tests, and can create Git commits. /api manages providers, models, login, and thinking settings; /session handles history, switching, and exports; /memory and /profile retain longer-term patterns and working preferences. /agent spawns parallel sub-agents coordinated with file locks, Git locks, and rate limiting, while tmux, GNU Screen, or Zellij can present their live output. /mcp connects external Model Context Protocol servers, /skills manages custom skills loaded from Git repositories, /spec drives the OpenSpec lifecycle, and /undo reverts changes from the preceding turn. It can also fetch and analyze web content or run AI tasks on remote systems over SSH, producing file changes, command and test results, and Git operations.
- A developer maintaining software over SSH, tmux, or a headless Linux server who wants repository investigation and fixes without leaving the terminal.
- A code maintainer who wants an AI to inspect a project, submit an implementation plan for approval, then edit files, run tests, and commit the result.
- An individual or team handling several coding tasks concurrently who needs sub-agent coordination backed by file locks, Git locks, and rate limiting.
- A developer who needs to switch among OpenAI, Anthropic, Google Gemini, GitHub Copilot, OpenRouter, local llama.cpp, or LM Studio configurations.
- A security-conscious engineer who wants secret redaction, command-risk analysis, path authorization, sandbox restrictions, or Docker isolation.
- An operations-oriented developer who wants to deploy CLIO over SSH, perform a task on another machine, and retrieve the results.
What are this agent's strengths and limitations?
- It runs directly in local shells, SSH sessions, tmux, Docker, and headless servers instead of requiring a desktop GUI.
- The workflow covers repository investigation, approval-based planning, editing, testing, Git commits, and turn-level undo.
- Sixteen provider configurations are documented, including native adapters for Anthropic, Google, and NVIDIA and keyless local options through llama.cpp and LM Studio.
- Parallel agents use file locks, Git locks, and rate limiting, with live output available through tmux, GNU Screen, or Zellij.
- Its defense-in-depth controls include secret redaction, command-risk classification, path authorization, sandbox mode, container isolation, and invisible-character filtering.
- Native execution is documented only for macOS 10.14+ and modern Linux; native Windows support is not described.
- Although the Perl application uses core modules, the complete environment still depends on Perl 5.32+, Git, curl, and standard Unix tooling.
- Most hosted providers require separate API credentials, while GitHub Copilot requires browser-based OAuth; service costs and quotas depend on the selected provider.
- Because CLIO can execute shell commands, alter files, and operate Git, adopters must review plans and authorization requests carefully.
- Remote execution, multiplexed live output, and full container isolation add SSH, tmux/Screen/Zellij, or Docker setup when those capabilities are needed.
How do you install or deploy this agent?
Run ./check-deps to verify the required tools. On macOS, execute brew tap SyntheticAutonomicMind/homebrew-SAM followed by brew install clio. For a manual installation, run git clone https://github.com/SyntheticAutonomicMind/CLIO.git and then cd CLIO && sudo ./install.sh. The documented container invocation is docker run -it --rm -v "$(pwd)":/workspace -v clio-auth:/root/.clio -w /workspace ghcr.io/syntheticautonomicmind/clio:latest --new. Native use requires macOS 10.14+ or modern Linux, Perl 5.32+, Git, curl and other standard Unix tools, plus an ANSI-compatible terminal.
How do you use this agent?
For GitHub Copilot, run ./clio in the repository, enter /api login, and complete the OAuth flow in the browser. For another API provider, start ./clio, then enter /api set provider openai, /api set key YOUR_API_KEY, and /config save; replace openai and the placeholder with the chosen provider and its credential. Local llama.cpp and LM Studio configurations do not require an API key. Start a fresh session with ./clio --new and try Read this project and tell me how configuration is loaded. as the first task. Use ./clio --resume for the latest saved session, ./clio --debug for debugging, ./clio --enable file_operations to limit the enabled tools, or ./clio --disable web_operations to block web operations.
FAQ
Am I locked into a single model vendor?
Will CLIO modify a project without review?
Does my code remain on my machine?
How can I recover from an incorrect edit?
/undo to revert the AI changes from the preceding turn. CLIO also exposes Git status, diff, commit, branch, and stash operations for version-controlled recovery workflows.Can I restrict what CLIO is allowed to do?
--enable and --disable controls for tool categories. --sandbox blocks web, remote, and agent access while restricting file operations to the project directory, and Docker is available for operating-system-level isolation.