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odai

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.

Why Use It

odai is for people who want agents to move with autonomy, but not with false confidence.

It helps an agent:

• ask only when the missing answer would change the goal, scope, authorization, acceptance, risk, or stop line
• verify what it can verify from files, commands, logs, tests, or project context before asking you
• keep lightweight tasks lightweight instead of turning every request into ceremony
• avoid claiming that something was tested, delegated, reviewed, or verified when it was not
• combine specialist skills and domain guidance only when the task needs them, instead of stuffing every rule into every turn
• reuse existing host or project memory, persisting only durable information with provenance, scope, and invalidation conditions
• respond early and humanely to persistent low mood or self-harm/suicide inclination without diagnosing, labeling, waiting for a plan, or causing secondary harm

The Dao of odai

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:

• Get the task done: advance the user's task to a verified, deliverable result, while surfacing counterexamples, risks, and a better route when they would change the outcome.
• Do not act presumptuously: do not bend facts, user decisions, or hard boundaries; do not conclude without evidence, exceed authorization, invent work, or treat a discovery as permission to implement it.

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.

Operating Standard

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.

Product Goal

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.

30-Second Start

Install the unified entry point:

npx skills add https://github.com/orziz/odai --skill odai

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.

DeepSeek Harness packages

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 Plugin command requires pnpm on PATH; the Agent installer supports exactly dsh@0.1.0-rc.7, dsh@0.1.1-rc.1, and dsh@0.1.1-rc.2. Each package already includes the canonical Odai skill and shared DSH runtime, and existing installations keep that bundled skill as the default. The Agent preserves every capability from the pinned DSH Standard preset and adds Odai as a scoped extension. Plugin needs neither a separate skill nor Agent; Agent needs neither a separate skill nor Plugin. Choose Plugin for profile-wide behavior or Agent for a selectable preset. Installing both is normally redundant and is only for a deliberate combination of those scopes. 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; executor remains same-turn because writes are controller-owned. Later requests stay ordinary: role words are not commands, task state selects direct, inline, same-turn, or child dispatch; read-only same-turn responsibilities hand their result back to the controller or authorized executor, an identical planner/controller model is not called twice, and an already-authorized implementation continues automatically 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.

Host Capability Routing

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.

The controller is the persistent task thread that owns the goal, global state, corre