Yolop

A terminal coding agent built on everruns-runtime. One binary that plans, edits, runs, and verifies code in your repository — autonomous by default, with persistent sessions, agent skills, MCP servers, and editor integration over the Agent Client Protocol.

Origin of the name

yolop comes from the Ukrainian Йолоп: a dummy, fool, or not-too-bright person. The name was meant to sound clever and funny in Ukrainian while also describing the agent's starting point: yolop does not believe in per-tool approval pop-ups. It uses an AI-judgement approach instead — autonomous by default, with soft approval for critical moments when you want spoken consent and an audit trail.

Install

brew install everruns/tap/yolop

Works on macOS (arm64/x86_64) and Linux (x86_64). If your Homebrew enforces tap trust checks, trust the tap once first with brew trust --tap everruns/tap. Building from source instead? cargo install yolop --locked.

Quick start

cd your/repo
yolop

First launch with no credentials opens a guided, keyboard-driven setup: provider → credentials → model. Or set a provider key and go:

OPENAI_API_KEY=sk-… yolop

yolop -C /path/to/repo        # work in a different workspace
yolop -p "summarize the build setup"   # one-shot, no TUI, prints to stdout
yolop --provider llmsim -p "hi"        # offline demo, no API key required

Features

Agent core

• Autonomous by default — yolop runs writes, edits, deletes, and bash commands without prompting. A standing write blocklist rejects writes into .git/, node_modules/, target/, dist/, build/, .next/, .venv/, venv/, .tox/, .gradle/ at any depth; reads are unrestricted inside the workspace.
• Soft approval — an optional spoken-consent layer for critical actions. yolop batches the safe work and pauses to ask, in plain chat, only before destructive or outward-facing steps; you approve by replying "yes". The paranoia level (protective / normal / off) is shown in the status bar and set with /setup approval <level> (or just by telling yolop to be more or less careful). See Soft approval below.
• TUI chat (ratatui): scrolling transcript, multiline composer, status bar (with a bg count whenever the session has background tasks), slash commands (/help, /tools, /mcp, /cwd, /setup, /model, /effort, /goal, /shell, /background, /clear, /quit), a read-only background-tasks panel toggled with Ctrl+B, !<command> as a direct shell shortcut, and natural-language requests for terminal actions such as "exit" or "clear the screen".
• Side questions — /btw <question> answers a question about the current session out-of-band: same context as the main task, no tools, and nothing added to the conversation history.
• Goal loops — /goal <condition> keeps working across turns until a separate evaluator model confirms the condition from the transcript; use /goal for status and /goal clear to stop early. Works in --print mode (yolop -p "/goal …"). See specs/goal.md.
• Planning — write_todos keeps multi-step tasks on track, and loop detection stops the model from retrying the same failing tool call.
• One-shot mode — --print runs a single prompt non-interactively, for scripts and CI.

Tools

• Filesystem — read_file, write_file, edit_file, list_directory, grep_files, delete_file, stat_file, backed by the real workspace disk.
• Repo map — repo_map and repo_symbols build an on-demand multi-language symbol overview for broad codebase orientation before targeted grep/read.
• AST grep — ast_grep runs read-only structural pattern search with ast-grep syntax across Rust, Python, TypeScript/TSX, JavaScript/JSX, C#, Go, CSS, HTML, and Bash.
• LSP (optional, off by default) — real language servers (rust-analyzer, typescript-language-server, pyright, gopls, clangd, or any configured binary) behind lsp_diagnostics, lsp_definition, lsp_references, lsp_hover, lsp_rename (workspace-wide, fixes every reference), lsp_symbols, and lsp_code_actions. Servers spawn lazily per language on first use. Enable with [[capabilities]] ref = "lsp" in settings.toml. See specs/lsp.md.
• Shell — bash -lc from the workspace root, with a 120 s wall-clock timeout and per-stream 1 MiB output cap; large output is spilled to disk under the session folder and stays readable for model tool calls. Use /shell <command> or !<command> in interactive sessions to run a command directly with bounded inline output.
• Background tasks — spawn_background runs a shell command detached from the current turn (e.g. gh pr checks <pr> --watch waiting on CI): it streams to a session-file log, writes a result.json, and tracks a background session task. Inspect and control them with list_tasks, get_task, and cancel_task (the /background command and the Ctrl+B panel list them). A task's result survives a restart. When a task finishes while the session is idle, yolop proactively wakes the agent with a turn so it reacts without waiting for your next prompt (turn off with the proactive_wake setting). See specs/background.md.
• Web — web_fetch (HTTP GET/HEAD with markdown/text conversion, DNS-pinned SSRF protection) and duckduckgo_search (free, no API key). Setting EVERRUNS_SYSTEM_ALLOWLIST_ENABLED=true restricts web_fetch to the runtime's curated allowlist of well-known public resources (package registries, source hosting, AI/cloud provider APIs, OS mirrors); off by default.

Context engineering

• AGENTS.md — project instructions re-read every turn.
• Workspace context — root, shell, local date/timezone, Git identity and branch injected automatically.
• Memory — a central, structured MEMORY.md of durable, cross-session user memories, each with a title, timestamp, and body. Managed in natural language ("remember that I prefer terse answers") via the remember / recall / forget tools. Only memory titles are injected each turn (progressive disclosure); bodies are recalled on demand, so the prompt stays small however much you remember. Tunable through the generic capability-config system (disclosed_titles, recall_limit, soft_cap). See specs/memory.md.
• Skills — SKILL.md files discovered from workspace (.agents/skills/), global (<config_dir>/yolop/skills/), and system (bundled) scopes, exposed via list_skills, read_skill, write_skill, and activate_skill. Workspace/global skills installed after startup are available immediately; the bundled skill-management skill covers search, npx-style imports, and upgrades. See specs/skills.md.
• Infinity context — older history is trimmed out of the live prompt but stays queryable via query_history, so long sessions don't hit the wall.
• Tool search — provider-agnostic deferred tool loading: core file/shell tools stay loaded, long-tail tools are hidden until the model pulls them in on demand, saving input tokens on every provider. See specs/tool-search.md.
• Prompt caching — Anthropic prompt-caching markers out of the box.

Extensibility

• MCP servers — extra tools from local (stdio) or remote (HTTP) Model Context Protocol servers via .mcp.json (see MCP servers).
• Hooks — workspace and global hook files can block, mutate, or audit agent actions through the upstream user_hooks capability. Configure them by chatting with yolop or by editing hooks.json. See docs/features/hooks.md.
• Editor integration — --acp speaks the Agent Client Protocol over stdio, so editors such as Zed can drive yolop as an external agent (see Editor integration).
• Sessions — every run writes a durable per-session event log; resume any conversation with --session <id> (see Session persistence).

Providers

Provider	Credential	Default model
OpenAI	OPENAI_API_KEY	gpt-5.5
Codex subscription	browser/device ChatGPT login or CODEX_ACCESS_TOKEN	gpt-5.5
Anthropic	ANTHROPIC_API_KEY	claude-sonnet-4-5
OpenRouter	OPENROUTER_API_KEY	openai/gpt-5.5
Google	GEMINI_API_KEY / GOOGLE_API_KEY	gemini-2.5-flash
Ollama	OLLAMA_BASE_URL / OLLAMA_API_KEY	llama3.2
Custom	CUSTOM_BASE_URL (+ optional CUSTOM_API_KEY)	— (set via /setup)
llmsim	none (offline simulator)	—

Pick explicitly with --provider, override the model with -m/--model. Codex subscription signs in through ChatGPT and uses the Codex backend directly; it does not shell out to the Codex CLI. Custom is any OpenAI-compatible Chat Completions endpoint (vLLM, llama.cpp, LM Studio, hosted gateways, …): point CUSTOM_BASE_URL at it or configure the base URL, optional key, and model interactively via /setup.

Git attribution

Enabled by default and configurable. When yolop creates commits, it keeps your git author/committer identity and appends Co-Authored-By: yolop <yolop@everruns.com> once. PR descriptions created or edited through gh get a Generated with yolop footer. Disable with /setup attribution off.

Soft approval

Soft approval is prompt-engineering, not a hard gate: yolop is told, in its system prompt, to batch safe work and pause for spoken consent only at the critical moments. The model decides what is critical; you approve in plain language ("yes", "approved"); each granted approval is recorded to the session event log for audit (via the record_approval tool). There is no separate approval UI — consent lives in the conversation.

A single central level, approval_mode, tunes how cautious yolop is:

Level	yolop pauses before…
protective	any state-changing action (writes, commits, pushes, installs)
normal	only destructive/irreversible or outward-facing actions (the default)
off	nothing — fully autonomous, no soft-approval prompt

The current level is always shown in the status bar. Change it with /setup approval <protective\|normal\|off>, or just ask yolop to be more or less careful ("stop asking me", "yolo mode") — it switches the level itself. The setting is saved to settings.toml, so it persists across sessions.

Soft approval is judgement, not a guarantee. For deterministic enforcement (hard-blocking a tool), use hooks; the two compose. For the public user-facing details, see Approvals.

Editor integration (ACP)

yolop implements the agent side of the Agent Client Protocol. Launch it with --acp and it speaks newline-delimited JSON-RPC 2.0 over stdin/stdout: the editor performs the initialize handshake, opens a session with session/new, and sends turns with session/prompt; yolop streams back assistant text, reasoning, tool calls, and plans as session/update notifications. Editors can also load an existing yolop session with session/load; yolop replays the persisted conversation history and continues from the same JSONL session log used by CLI --session.

To set up Zed:

yolop into zed

That adds a custom ACP agent server to ~/.config/zed/settings.json using the current yolop executable, preserving any existing env and extra settings on re-run. Then pick yolop in Zed's agent panel. See specs/acp.md for the full protocol surface, mappings, and current limitations.

MCP servers

Yolop pulls in extra tools from MCP servers — remote (Streamable HTTP) and local (stdio, a child process) — configured in the standard .mcp.json shape every MCP client understands. Two scopes are read and merged (workspace overrides global by name):

• workspace: <workspace_root>/.mcp.json
• global: <config_dir>/yolop/mcp.json (e.g. ~/.config/yolop/mcp.json)

{
  "mcpServers": {
    "docs": {
      "type": "http",
      "url": "https://example.com/mcp",
      "headers": { "Authorization": "Bearer ${DOCS_TOKEN}" }
    },
    "fs": {
      "type": "stdio",
      "command": "mcp-server-filesystem",
      "args": ["${WORKSPACE}"],
      "env": { "RUST_LOG": "info" }
    }
  }
}

• type defaults to http; HTTP servers need a url, stdio servers need a command.
• String values support ${VAR} expansion from the environment, so secrets stay out of the file (an unset ${VAR} is left as-is so it's easy to spot).
• Discovered tools are exposed to the model as mcp_<server>__<tool>; /mcp lists the configured servers.

Trust model: HTTP requests keep yolop's DNS-pinned SSRF protection; stdio servers run local processes you listed yourself, so authoring .mcp.json is the act of consent. MCP tools run autonomously like the rest of yolop's tools. See specs/mcp.md.

Reference

Flags

Flag	Description
-C, --cwd <PATH>	Workspace root (default: current dir)
--provider <P>	Force anthropic, codex, openai, google, openrouter, ollama, custom, or llmsim
-m, --model <ID>	Override the model id for the chosen provider
-p, --print <PROMPT>	Run one prompt non-interactively and print the result
--acp	Speak the Agent Client Protocol over stdio (for editors like Zed)
--session <ID>	Resume a previous session by id
--session-dir <PATH>	Override the parent directory for session folders
--reasoning-effort <E>	Reasoning effort override when the selected model profile supports it
--trajectory-out <PATH>	Write the session as an ATIF v1.7 trajectory JSON file at end of run (interactive and --print)

Commands

Command	Description
yolop version	Print yolop, commit, and runtime versions
yolop into zed	Configure yolop as a custom ACP agent in Zed

RUST_LOG is honored for the underlying tracing layer (writes to stderr).

Provider env vars

Env var	Effect
OPENAI_API_KEY	Select OpenAI unless --provider overrides
CODEX_ACCESS_TOKEN	Select Codex subscription auth unless a higher-priority provider is configured
ANTHROPIC_API_KEY	Select Anthropic when OpenAI is not configured
OPENROUTER_API_KEY	Select OpenRouter when OpenAI/Anthropic are not configured
OPENROUTER_BASE_URL	Optional, defaults to https://openrouter.ai/api/v1
GEMINI_API_KEY / GOOGLE_API_KEY	Select Google Gemini via its OpenAI-compatible endpoint
GOOGLE_BASE_URL	Optional, defaults to https://generativelanguage.googleapis.com/v1beta/openai
OLLAMA_BASE_URL	Select Ollama, defaults to http://localhost:11434/v1
OLLAMA_API_KEY	Optional, defaults to ollama for local Ollama
CUSTOM_BASE_URL	Select the custom OpenAI-compatible endpoint (beats the saved base URL)
CUSTOM_API_KEY	Optional key for the custom endpoint (a placeholder is sent otherwise)
EVERRUNS_CLI_MODEL	Override the auto-selected default model (beats the saved model)
EVERRUNS_CLI_REASONING_EFFORT	Reasoning effort override when the selected model profile supports it

Settings

A small TOML settings file persists the preferred provider, per-provider model picks, custom endpoint base URLs, the soft-approval level (approval_mode), Codex subscription login metadata, and (optionally) provider API tokens across runs: <config_dir>/yolop/settings.toml — ~/.config/yolop/settings.toml on Linux, ~/Library/Application Support/yolop/settings.toml on macOS, %APPDATA%\yolop\settings.toml on Windows.

The TUI's /setup, /model, and /effort commands update the active provider, saved API keys, current model, reasoning effort, or offline demo mode. The /setup provider picker shows which providers are already connected (env key, saved key/login, or no key needed); selecting a connected one jumps straight to model selection, and c opens key/base-URL configuration for any provider. Provider, model, and custom base URL choices are written to this file.

The model picker queries the provider's models API live (OpenAI, Anthropic, and OpenRouter via the everruns drivers; Ollama, Gemini, and other OpenAI-compatible endpoints via GET <base>/models), enriched with human-readable names and descriptions from the everruns model profiles. A curated shortlist is shown until the API responds — or instead of it, when listing is unavailable — and the "Custom..." entry always accepts any model id.

Provider resolution at startup:

1. --provider flag (always wins)
2. Saved default_provider setting (the legacy provider key is still read)
3. Auto-detect: the first provider in the order OpenAI → Codex → Anthropic → OpenRouter → Google → Ollama → Custom with either a matching env var or a saved token/login/base URL (the provider order decides the tiebreak, not the credential source)
4. Fall back to OpenAI's default model and open setup so a provider/API key can be configured

The model saved by /setup model for the resolved provider is restored, unless -m/--model or EVERRUNS_CLI_MODEL overrides it. When the resolved provider has no saved model, the global default_model setting (if set) is applied as a cross-provider fallback. At runtime, the per-provider env var (OPENAI_API_KEY, etc.) always beats the saved token, so a per-run env override is always possible. /model <id> opens the model picker prefilled for the active provider. Reasoning effort can be changed at runtime with the /effort modal or /setup effort <level> when the selected model profile exposes effort levels. The available values and default come from that model profile, so they can vary by model.

/setup can store an API token under [tokens] in the settings file. The Codex subscription provider stores OAuth data under [codex_auth] instead. file is written with 0o600 on Unix (owner-only) and stored token values are never echoed — but it is plain text on disk, so treat it the same way you would ~/.aws/credentials.

The settings file is also schema-described: every key carries a title, description, type, default, and examples (see specs/configuration.md). yolop itself can read and edit it through the get_config and set_config tools or the yolop-config skill — for example, "use anthropic by default", "store my OpenAI key", or "set the default model to gpt-5.5 high". Unknown keys in the file are ignored, never fatal, so the format stays forward-compatible.

Session persistence

Every run writes a durable per-session folder under the platform-native user data directory:

OS	Default location
Linux	$XDG_DATA_HOME/yolop/sessions/<session_id>/ (typically ~/.local/share/…)
macOS	~/Library/Application Support/yolop/sessions/<session_id>/
Windows	%APPDATA%\yolop\sessions\<session_id>\

The event log lives at <session_folder>/events.jsonl; the workspace root is stored in <session_folder>/workspace.json; large tool output is spilled under <session_folder>/outputs/. On Unix the session folder is 0o700 and the log and workspace metadata are 0o600 (owner-only). The log keeps everything needed to restore the transcript and provider continuation state on resume — including prompts, tool arguments and output, and reasoning artifacts.

To continue a previous conversation:

yolop --session session_019e3db018a17450aba5407af5777237

When no -C/--cwd is supplied, resume uses the workspace root saved for that session instead of the shell's current directory. Pass -C <PATH> with --session to intentionally move the resumed session to a different workspace.

--session-dir <PATH> overrides the parent storage location (useful for keeping per-workspace session histories in <workspace>/.yolop/sessions/).

Treat session logs as you would shell history. They contain every prompt you typed, every string passed to bash / write_file / web_fetch, tool output, and reasoning artifacts — deliberately unredacted, because providers need them to resume encrypted reasoning across sessions. There is no retention policy or rotation. If a session should not be persisted, point --session-dir at a path you can wipe (e.g. a tmpfs) or delete the JSONL after the run.

Contributing

Development setup, validation commands, and local smoke tests live in CONTRIBUTION.md.

Please report vulnerabilities through SECURITY.md, and follow the project CODE_OF_CONDUCT.md when participating.

Benchmarking

evals/ holds yolop's Mira eval studies. evals/swebench_verified/ benchmarks yolop on SWE-bench Verified and, behind the same interface, other terminal agents (claude-code, codex, pi) for head-to-head comparison — recording resolved-rate plus cost, tokens, turns, and tool usage per run. The mira host CLI drives it. See evals/README.md; evals/swebench_verified/bootstrap.sh sets it up.

Releases

Yolop ships to the everruns/homebrew-tap Homebrew tap and to crates.io as the yolop crate. See specs/release.md for the release procedure and CHANGELOG.md for what shipped in each version.

License

MIT — see LICENSE.