oh-my-agent (dsh)

# Windows (PowerShell)
irm https://raw.githubusercontent.com/first-fluke/oh-my-agent/main/cli/install.ps1 | iex

# Any OS with bun installed: the same setup, plus the global `oma` command
bun install --global oh-my-agent
oma

On Windows the installer hides Antigravity, Hermes, and Kimi, and the hook wrapper is a bash script. The default Aside browser MCP installs through bash, so deselect it if you have no bash.

• Installs bun (required). Tries uv, Serena (uv tool install), and CUE (brew install cue or winget), and continues with a warning if any of them fails.
• Pre-selects the Aside browser MCP in the interactive setup, and installs it with curl -fsSL https://releases.aside.com/install.sh | bash only if you keep it selected. Deselect it in the browser MCP step, or change it later with oma update mcp.
• Uses AgentMemory for semantic memory, which runs bun install -g @agentmemory/agentmemory and registers it as a login service (launchd, systemd user unit, or Windows scheduled task). Choose provider none or set OMA_NO_AGENTMEMORY=1 to skip it.
• Asks before linking skills into home-directory vendor folders (Antigravity, Hermes, Kimi). In $HOME without --global it asks for confirmation.
• Writes some files outside the project without asking: ~/.claude.json (marks the project as a trusted Claude Code workspace), ~/.serena/ (OMA context, answer-size floor, project registration), ~/.cursor/cli-config.json (turns off Cursor's commit attribution), ~/.grok/config.toml (telemetry), and ~/.gemini/antigravity-cli/ (HUD), each only for a vendor you selected.
• Writes telemetry opt-outs into vendor settings (Claude DISABLE_TELEMETRY=1, which also turns off Claude Code Remote Control; Gemini, Qwen, Codex, and Grok usage stats). Set telemetry: true to keep vendor defaults.
• Disables Qwen Code automatic memory saving by adding memory.enableManagedAutoMemory: false when the setting is absent. Explicit true or false preferences and other memory settings are preserved.
• Adds unset Claude Code settings to .claude/settings.json, including skipDangerousModePermissionPrompt: true, effortLevel: high, cleanupPeriodDays: 180, and env flags that turn off auto memory, adaptive thinking, error reporting, and built-in git instructions. Values you already set are kept.
• Adds a co-author trailer: Claude Code's commit attribution becomes Co-Authored-By: First Fluke <our.first.fluke@gmail.com> and PRs get a "Generated with oh-my-agent" line. Set scm.co_author.enabled: false to turn this off.
• Installs a commit-msg guard in .githooks/ that rejects unlisted Co-authored-by addresses, and sets git config --local core.hooksPath .githooks when no other hooks are active. Set scm.co_author.enforce_hook: false to opt out.
• oma update updates the oma CLI in the background (auto_update_cli: false or OMA_SKIP_VERSION_CHECK=1 to stop it) and runs uv tool upgrade serena-agent --prerelease=allow (serena.auto_update: false).
• With Serena in the default bridge mode, the first agent session that starts a shared Serena server registers a cleanup timer that stops idle shared Serena servers every 5 minutes (launchd dev.oma.serena-daemon-gc, systemd user timer oma-serena-daemon-gc.timer, or Windows scheduled task OMA Serena Daemon GC). Set serena.mode: stdio to skip the shared server and its timer. oma uninstall does not remove the timer.
• Non-interactive runs (-y, OMA_YES=1, CI=true) use the All skill preset, model_preset: auto, and Python as the backend language. They select no browser MCP (and skip the Aside install script) unless mcp.devtools_browsers already lists one.

Of the named presets, only All includes coordination, orchestration, docs, security, refactor, explanation, recap, video, slide, and skill-creation (or pick them under Custom). Research and Content lack the skills behind /plan, /review, /debug, /architecture, and /brainstorm. See Workflows that need skills outside a preset.

The infra engineer (tf-infra-engineer) is told to ask before any destructive or production apply or destroy. The remaining skills (brainstorm, security, scm, dev-workflow, observability, explanation, recap, translation, coordination, orchestration, skill-creation, content and media) have no dedicated role. Your agent loads them itself, and for most of them the skill injector suggests the right one from your prompt.

Trigger accuracy is measured, not assumed: oma verify triggers scores the detector against a labeled English and Korean corpus of 212 prompts, and CI fails above 10% false fires or 20% missed fires. Last measured: 0% missed-fire, 5.3% false-fire. Full reference: Workflows.

/stack-set reads your manifests and writes stack-specific references for the backend, frontend and mobile skills. In a monorepo, frontend, backend and mobile engineers are pointed at their workspace (pnpm, npm/yarn/bun workspaces, lerna, nx, turbo, mise.toml).

These pipelines report a missing source or vendor key instead of silently returning a thinner result.

oma hook probe checks that oma's prompt hooks accept each runtime's hook input (it does not launch the runtime). Which hooks each runtime wires is in Host differences.

• oma agent spawn <role> "<task>" <sid> runs a role on Antigravity, Claude, Codex, Cursor, OpenCode, Qwen, Grok or Pi, with --isolation worktree and --fallback-vendors. oma agent parallel runs several at once.
• Add --read-only to require a vendor restriction before launch. Codex uses its read-only sandbox, Claude uses plan mode, and Pi excludes edit, write, bash, and powershell. Other CLIs require an explicit read_only_flag; missing, empty, or known conflicting flags stop dispatch. Custom flags declare support in your CLI or wrapper. Pi's tool exclusions do not restrict arbitrary extension or MCP tools; OMA does not add an operating-system sandbox.
• oma state list --all-projects and oma state get <sid>: sessions and every recorded event.
• oma dashboard terminal / oma dashboard web: live agent status (the web dashboard listens on 127.0.0.1 only). Dashboard guide.
• oma stats get (productivity metrics), oma retro (a git retrospective), oma recap --window 7d (what you did across AI tools).
• oma visualize --affected <paths>: which skills, workflows, agents and checks depend on the .agents/ files you changed.

Agents coordinate through plain files in .agents/state/, with no outside service. /tools turns MCP tools on or off in plain language. Details: Capability Providers.

• oma skill eval measures a skill's lift over a baseline on held-out tasks. oma skill optimize proposes edits that raise it, and --apply keeps them (skill-eval guide).
• oma harness evolution enable --max-dispatches <n> schedules a nightly cycle that turns failed runs into regression fixtures and applies skill improvements that pass evaluation as project overlays. Add --mode propose to only record them.
• oma emit exports the .agents/ source as an Agent Skills package, an Agent Plugins package, a Claude Code plugin marketplace, or AGENTS.md.

• One user-owned .agents/oma-config.yaml survives updates (only oma update --force resets it); private .local.yaml or .local.cue overlays can sit on top of it. language sets the response language.
• 13 project rules (backend, commit, database, debug, design, and more) load as native rules in Claude Code and Cursor, and are indexed in the managed AGENTS.md block written for Codex, Qwen Code and Pi.
• Updates keep config and migration backups in .agents/backup/; shipped skills and workflows are replaced in place, so keep local changes outside them. oma uninstall --dry-run shows what would be removed. first-fluke/oma-update-action@v1 runs oma update in CI and opens a PR.

native = oma writes the runtime's own config files; adapter = oma also adds hook or agent shims. Amp reads .agents/skills/ by itself and is not an installer target.

Claude Code native + adapter	Codex CLI native + adapter	Antigravity native SSOT	Cursor native + adapter	Qwen Code native dispatch	DeepSeek Harness Cordis plugin
Pi native-compatible	OpenCode native-compatible	Amp reads .agents/skills	GitHub Copilot symlinked skills	Grok Build native hooks	Kiro CLI native hooks + agents

_{& more}

model_preset in .agents/oma-config.yaml chooses which model each agent role uses. The default, auto, follows the running runtime's own agent and model settings.

language: en
model_preset: auto   # auto | free | antigravity | claude | codex | cursor | kiro | mixed | qwen | <custom_presets key>

# Optional per-agent overrides; they win over the preset
agents:
  backend: { model: openai/gpt-5.5, effort: high }

• mixed uses Claude for orchestrator, architecture, QA, PM, and docs, and Codex gpt-5.5 for implementation roles, so it needs both Claude Code and Codex CLI.
• free routes through a FreeLLMAPI gateway and needs FREELLM_API_KEY plus a running server.
• kiro is not in the installer menu; set it in the config file.
• oma doctor --profile prints the resolved model for each role.
• Full guide: Per-agent models

Limits to know:

• The Stop gate applies only to the persistent workflows (/orchestrate, /work, /ultrawork, /ralph). Without oma goal set --gate, it only re-prompts the agent to continue. /ultrawork tells the agent to set a gate when the project has a cheap check, but nothing enforces it. Run oma goal set --gate test yourself if you want to be sure; the other persistent workflows never set one.
• Only the typecheck, test, and lint keywords are accepted, and they run the package.json script of that name. No package.json, or no script with that name, means the gate is not run. Non-JS projects need a package.json wrapper script.
• The block is released and logged as failed after 5 reinforcements, after 2 hours, or when --budget-minutes runs out, so a permanently red gate cannot trap you.
• Budgets: session.quota_cap caps tokens, spawn count, and per-vendor tokens; the orchestrator refuses the next spawn when a dimension is exceeded.

Artifact gate. A missing artifact means the phase did not run, whatever the narration says. The refactor check also passes as skip-recorded when the session log records a REFINE skip reason.

Prompted judge. The /ralph workflow prompt tells the orchestrator to spawn the judge as a separate agent with fresh context, briefed on the criteria only (never on what the implementer claims it fixed), and to re-verify every criterion each iteration, including earlier PASSes, because fixing C2 is how C1 silently regresses. Nothing checks that the spawn happened: oma ralph verify gates the EXEC artifacts, not the judge, and a runtime that cannot spawn subagents is told to judge inline and record ralph.judge-inline-fallback. /ralph stops after 5 iterations with a partial report.

Event log. Find the session with oma state list and read it with oma state get <sid>. Each event is stamped with vendor and runtime session id. The file's location depends on OMA_HOME, OMA_STATE_HOME, OMA_PROFILE, and older project-local session folders, so don't hard-code it.

Per-agent checks. Types: backend, frontend, mobile, qa, debug, pm. The command exits 1 when any check fails; TODO/FIXME Comments and Inline Styles only warn.

• backend: <Language> Syntax, SQL Injection (raw SQL patterns), and <Language> Tests, from the commands in stack/stack.yaml. Without that file (generate it with /stack-set) they are skipped.
• frontend: the stack/stack.yaml syntax and test commands (under oma-frontend, or angular-developer when that skill is installed), or TypeScript (tsc --noEmit) and Frontend Tests (Vitest). Inline Styles and Any Types always run.
• mobile: the stack/stack.yaml syntax and test commands, or Flutter/Dart Analysis and Flutter Tests.
• debug: Python Tests (pytest through uv) or Frontend Tests (Vitest).
• pm: PM Plan (the plan file is valid JSON).
• qa: no mechanical checks.

flowchart TD
    S[Agent tries to stop] --> P{Persistent workflow active?}
    P -- no --> A[Stop allowed]
    P -- yes --> D{User or agent said workflow done?}
    D -- yes --> A
    D -- no --> R{Budget spent, state older than 2 h, or 5 blocks reached?}
    R -- yes --> F[Stop allowed, logged as gate.failed]
    R -- no --> G{Gate set and package.json script exists?}
    G -- no --> B1[Blocked: workflow still active]
    G -- yes --> X{Script exits 0 within 25 s?}
    X -- yes --> OK[Stop allowed, logged as gate.passed]
    X -- no --> B2[Blocked with output tail, logged as gate.failed]

No. See Skill presets; All is the safe default.

oma doctor shows installed skills and warns when hooks can't find oma. During a persistent workflow, oma state list shows the active session and oma state get <sid> shows its gate events.

Usually, yes. Skills load only when a task needs them, but multi-agent workflows and fresh-context reviews spend more. In the one-prompt benchmark, oma cost 1.7x plain Claude Code.

Say "workflow done" (or "workflow complete" / "workflow finished", or the equivalent in the other supported languages), or delete .agents/state/<workflow>-state-<sid>.json. If you do neither, it releases on its own after 5 blocks or 2 hours.

oma update refreshes skills, workflows, and hooks and keeps your config (--with-new-skills adds skills new in the release; oma update mcp re-chooses the browser MCP). oma uninstall --dry-run shows what would be removed; oma uninstall removes it and keeps oma-config.yaml, mcp.json, and skills you wrote. More fixes: Troubleshooting.

Planning and choosing the next step stay with your agent's model; oma has no fixed workflow graph. What oma enforces outside the model: tool guardrails (secret and search guards), budgets, retry and stop limits, an event log, and, when you set a gate, a stop that waits for your own checks to pass.

• Li, X., Liu, Y., Chen, W., You, B., Di, Z., He, Y., Zheng, S., Choe, K. W., Sun, J., Wang, S., Tao, C., Li, B., Zhao, X., Geng, H., Wu, X., Zhou, J., Chen, X., Xing, H., Li, Y., … Song, D. (2026). SkillsBench: Benchmarking how well agent skills work across diverse tasks (Version 4) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2602.12670
• Yu, G., & Wang, X. (2026). Knows: Agent-native structured research representations (Version 1) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2604.17309
• Liang, Q., Wang, H., Liang, Z., & Liu, Y. (2026). From skill text to skill structure: The scheduling-structural-logical representation for agent skills (Version 4) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2604.24026
• Chen, C., Yu, Q., Gu, Y., Huang, Z., Li, H., Liu, H., Liu, S., Liu, J., Peng, D., Wang, J., Yan, Z., Meng, F., Qin, E., Che, C., & Hu, M. (2026). The scaling laws of skills in LLM agent systems (Version 1) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2605.16508
• Tang, L., Rashtchian, C., Ferng, C.-S., Tomkins, A., Juan, D.-C., & Vu, T. (2026). WikiSkill: Compiling agent experience into persistent knowledge for skill evolution [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2608.27454
• Huang, Z., Xu, J., Yang, Y., Gong, Z., Yang, Q., Tian, M., Wang, X., Lv, C., Gao, X., Dai, Q., Liu, B., Qiu, K., Yang, X., Chen, D., Zheng, X., & Luo, C. (2026). From raw experience to skill consumption: A systematic study of model-generated agent skills [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2605.23899
• Hong, D. B., Imani, A., & Ahmed, I. (2026). From anatomy to smells: An empirical study of SKILL.md in agent skills (Version 2) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2607.01456