odai is a governance-powered general task-execution framework for AI agents.
$ npx -y skills add orziz/odai --agent claude-code
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odai is a governance-powered general task-execution framework for AI agents.
It embeds governance into execution: align the real objective, facts, assumptions, authorization, risks, and acceptance; then choose the shortest sufficient path, combine the right capabilities, act, verify, and keep moving until the task is genuinely deliverable. It does not replace the model's judgment with a rigid workflow.
The short version: call /odai; governance stays nearly invisible on simple work, while ambiguity, complexity, risk, and domain needs automatically increase or reduce the depth of handling.
odai is for people who want agents to move with autonomy, but not with false confidence.
It helps an agent:
The user defines the task; evidence determines the route; methods adapt to circumstances; verification determines completion; boundaries determine where to stop—get the task done, without acting presumptuously.
This is not a collage of philosophical schools. It is one decision rule:
The person and the model work as partners toward a shared result, not through a one-way command chain. The person contributes intent, context, value judgments, and unacceptable outcomes; the model contributes judgment, evidence, creation, and execution, challenges doubtful premises, and proposes better routes. Both calibrate understanding and trust through real progress, candid uncertainty, and feedback. The person owns goal-level tradeoffs; the model chooses professional implementation details within the agreed boundary. Authorization is not blind obedience, and challenge is not a takeover.
odai is neither an echo of the user nor a reciter of rules. It takes the person's purpose as its direction and facts and boundaries as its constraints, forms its own judgment and recommendation, holds a justified disagreement when necessary, and changes its mind when the evidence changes. Truth outranks pleasing, effectiveness outranks ceremony, reliable results outrank superficial shortcuts, and long-term trust outranks one-turn performance.
The model's initiative is judged by net value. Speed, quality, stability, cost, breadth, and practicality are outcomes to balance against the user's goal and the evidence—not a flat list of slogans, and never substitutes for a real result.
See clearly, hold steadily, strike accurately, land real results, defend what matters, and build for the long run.
Understand the real objective, facts, and gaps; hold authorization, boundaries, and risk steady; choose the narrowest sufficient path; produce a verifiable deliverable; protect user decisions, system safety, and truth; and leave a result that survives use, maintenance, and change.
Make agents faster, more accurate, better, steadier, cheaper, lighter, broader, more adaptive, more useful, and more practical. These are not independent process targets. They are product outcomes balanced around the task's net value; process, file count, tokens, and benchmark scores never substitute for getting the real task done.
Install standalone governance:
npx skills add https://github.com/orziz/odai --skill odai
The source candidate separates optional orchestration into an installable sibling skill:
npx skills add https://github.com/orziz/odai --skill odai-orchestration
odai-orchestration depends on odai and adds responsibility presets and host routing adapters. Installing the skill does not change host settings. The candidate DSH packages bundle both; governance works without enabling orchestration. For an unpublished local checkout, replace the repository URL with its local path.
Then invoke it with /odai. That is the normal form in clients that expose skills as slash commands:
/odai update the onboarding flow copy.
Goal: make it clearer for first-time users.
Materials: current app files and README.
Constraints: do not change behavior yet; give me the proposed copy and risks first.
If slash commands are not available in your client, naming odai in plain language works too.
You do not need to know the internal structure or choose a methodology. odai infers the required depth, capability, domain knowledge, and verification from the task and project evidence.
DSH users can install either integration independently:
# Apply Odai to every agent preset in one profile
dsh plugin --profile web add odai-dsh-plugin
# Install a selectable, session-scoped Odai Agent preset
npx odai-dsh-agent install
The current 0.2.56 source candidate uses DSH 0.2.1-rc.2 as its minimum supported baseline. The Agent admits >=0.2.1-rc.2, including later prereleases, and both npm peers remain open (*). Later releases still need compatible host APIs and are not certified without testing. Earlier DSH versions are outside current support; published releases retain their historical compatibility entries. Odai owns its preset and preserves its capabilities without copying Standard or automatically adding its new tools. Control Center uses the Web transport while headless governance remains independent of it.
Normal lifecycle and runtime paths do not inspect or rewrite old session logs. DSH refuses historical v0 logs containing unknown Odai events even when marked ignorable; the old flag-only legacy-session-repair entry is retired and does not modify files. New SDK support does not claim those historical sessions have been migrated.
The Plugin command requires pnpm on PATH. Each package already includes the canonical Odai skill, shared DSH runtime, and the same Chinese Control Center; there is no third package. Plugin exposes Control Center automatically. Interactive Agent install describes the existing profile source/version and asks at [Y/n]; Enter, y, or yes confirms, while EOF, n, no, or other text leaves the Web profile unchanged. Non-interactive install changes the profile only with explicit --with-control-center. Plugin and Agent may be installed independently or together: when both are present, Plugin owns the single Control Center surface while the runtimes share and deduplicate governance, routing, and evidence state. The existing provider-neutral odai-cli remains a separate product.
Both DSH packages default output to soft concise. Users can explicitly select normal output or the optional economy mode, which combines concise presentation with a user-adjustable provider output ceiling: it defaults to 500 when economy is requested without another value. The ceiling never changes child-agent, compaction, checkpoint, or internal context budgets and may be exceeded or ignored by the provider. See dsh/README.md for the complete three-mode contract.
A complete independently installed Odai skill can update faster than either DSH package without changing the default. The user must explicitly ask Odai to switch the skill source to auto or user; auto can select compatible project .dsh/.agents bundles and newer user installs, while user ignores project roots. An explicit deployment path remains highest priority. Plugin and Agent deliberately installed together share one per-agent/per-turn snapshot, so prompt governance and routing role contracts cannot select different bundles.
Neither DSH package chooses responsibility models or dispatch overrides. Tell Odai naturally, for example, use provider/model for planning with high reasoning and dispatch planning as child; the runtime persists only those explicit choices for both surfaces. Researcher, planner, reviewer, and frontend can each use same-turn or child; optional creative supports only read-only child dispatch on API and local CLI routes, returning writing candidates, tradeoffs, or review findings. The controller owns integration, validation, and final delivery. DSH children remain read-only and can return unapplied patches when explicitly assigned patch preparation; research, planning, and review retain their narrower contracts. Later requests stay ordinary: role words are not commands, task state selects direct, inline, same-turn, or child dispatch; read-only same-turn responsibilities return only to the controller, an identical planner/controller model is not called twice, and the controller continues an already-authorized implementation after planning. If a needed responsibility is still unconfigured, Odai names it and asks for the model instead of claiming that route ran. Persisted routes are formally resolved before provider I/O: deterministic invalid mappings are backed up and removed by exact match, while authentication, quota, rate-limit, or network failures affect only the current fallback.
DSH human-safety continuity is separate from generic semantic memory. Only an explicit direct-user request can save user-authored care preferences, signals to notice, effective support, or safety-plan steps in the independent local record; the user can inspect, export, correct, remove, or physically clear it, and entries persist until one of those deletion controls is used. New sessions treat it as historical care preference, never as present-risk evidence, diagnosis, or a hidden score, and child agents never receive it.
See dsh/README.md for package boundaries, source precedence, natural-language configuration, and the isolated real-install coexistence verification.
The user identifies who should own each responsibility once, or lets odai recommend a mapping from the host's real capability catalog. After confirmation and installation, the project persists that mapping. Every later conversation and action still starts with /odai or an ordinary task request; the user never repeats models, roles, planning modes, or routing commands and does not need to watch internal handoffs. When models change, update the mapping once in place.
odai is a Claude Code plugin with 4 hand-picked skills, indexed on Flowy in the Agent Orchestration category. Install it with the command on its page. It includes odai-orchestration, odai, renwei. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
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