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PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

Decision Anchor

作者:zse4321バージョン 1.3.42i★ 1iクラウドで動く
レジストリ名com.decision-anchor/da

インストール方法

概要

作者による説明(英語の原文)

External anchoring layer: records AI agent accountability boundaries on both sides. Content-blind.

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: クラウドで動く
  • トランスポート: Streamable HTTP
  • カテゴリ: その他

インストール

使っているAIアプリを選んで、設定をコピーしてください。

チェック 5/5 合格 · 質問内容は提供元のサーバー(mcp.decision-anchor.com)を通ります

まず:どの AI を使っていますか?

使っているアプリを選ぶと、下に手順が表示されます。

Claude につなげます · 約 2 分

キー不要、インストール不要 · claude.ai かデスクトップアプリで一度設定すれば、チャットで使えます · 無料アカウントは 1 つまで

  1. Claude の Connectors ページを開く

    CustomizeConnectors

    CustomizeConnectors1+ Add2https://…3Add4
  2. 「+ Add」→「Add custom connector」を押し、この 2 つを入力

    ここからコピーして Claude の同じ名前の欄に貼り付け、Continue を押します

    Name · 名前Decision Anchor
    Remote MCP server URL · アドレスhttps://mcp.decision-anchor.com/mcp

    Authentication は Claude が検出したままにして Add を押します

  3. チャットで有効にする

    +ConnectorsDecision Anchor

  4. 試してみる

    Decision Anchor を使って、私に何ができるか教えて、1 つやってみせて

    ✓ Claude が Decision Anchor を使っていると言うか、回答に Decision Anchor のツール名が出れば接続成功です

メニュー名は 2026年11月11日 に Anthropic のヘルプページで確認 · アプリのバージョンにより画面が少し違うことがあります

ChatGPT は法人向けプランのみ接続できます

Web 版 ChatGPT Business・Enterprise・Edu で、ワークスペースの管理者かオーナーが追加します · Free・Plus・Pro の場合:あなたの ChatGPT プランではまだ MCP を自分でつなげません

  1. Web 版 ChatGPT で MCP の追加ページを開く

    Plugins+Add custom MCP server

    ChatGPTPlugins1+2https://…3Create4
  2. 名前とアドレスを入力

    名前を入れ、Connection にアドレスを貼り付け、注意事項にチェックして Create as a plugin を押します

    Name · 名前Decision Anchor
    Connection · アドレスhttps://mcp.decision-anchor.com/mcp
  3. チャットで Decision Anchor を選ぶ

    新しいチャットを開き、入力前にプラグインの一覧から Decision Anchor を選びます

  4. 試してみる

    Decision Anchor を使って、私に何ができるか教えて、1 つやってみせて

    ✓ ChatGPT が Decision Anchor を使っていると言うか、回答に Decision Anchor のツール名が出れば接続成功です

メニュー名は 2026年11月11日 に OpenAI のヘルプページで確認 · アプリのバージョンにより画面が少し違うことがあります

Claude Code につなげます · 約 2 分

キー不要、インストール不要

  1. ターミナルを開く

    Mac:Command+スペースで Terminal と入力 · Windows:PowerShell を開く

  2. このコマンドを貼り付けて Enter

    claude mcp add --transport http da https://mcp.decision-anchor.com/mcp
  3. Claude Code で /mcp と入力

    Decision Anchor が一覧にあり、接続済みと表示されれば OK です

  4. 試してみる

    Decision Anchor を使って、私に何ができるか教えて、1 つやってみせて

    ✓ Claude Code が Decision Anchor を使っていると言うか、回答に Decision Anchor のツール名が出れば接続成功です

メニュー名は 2026年11月11日 に Anthropic のヘルプページで確認 · アプリのバージョンにより画面が少し違うことがあります

Cursor につなげます · 約 2 分

キー不要、インストール不要

  1. このボタンで Cursor を開く

    Cursor で開く

    Cursor がインストールの確認をするので Install を押します

  2. Cursor の AI チャットを Agent モードで開く

  3. 試してみる

    Decision Anchor を使って、私に何ができるか教えて、1 つやってみせて

    ✓ Cursor が Decision Anchor を使っていると言うか、回答に Decision Anchor のツール名が出れば接続成功です

メニュー名は 2026年11月11日 に Cursor のヘルプページで確認 · アプリのバージョンにより画面が少し違うことがあります

VS Code につなげます · 約 2 分

キー不要、インストール不要

  1. このボタンで VS Code を開く

    VS Code で開く

    VS Code がインストールの確認をするので Install を押します

  2. VS Code の AI チャットを Agent モードで開く

  3. 試してみる

    Decision Anchor を使って、私に何ができるか教えて、1 つやってみせて

    ✓ VS Code が Decision Anchor を使っていると言うか、回答に Decision Anchor のツール名が出れば接続成功です

メニュー名は 2026年11月11日 に VS Code のヘルプページで確認 · アプリのバージョンにより画面が少し違うことがあります

Windsurf、Zed、Gemini CLI など MCP を使える他のアプリは追加方法がそれぞれ違います。アプリ一覧で確認してください

MCP を使えるアプリをすべて見る →

Web 経由でつなぐアプリ用のアドレス

アドレスhttps://mcp.decision-anchor.com/mcp

JSON 設定は下の「開発者向け」にあります

つまずいたら?Decision Anchor を使っている人に聞いてみましょう💬 ディスカッション →
開発者向け:ターミナルのコマンドと JSON 設定

Web 経由

Claude Code

claude mcp add --transport http da https://mcp.decision-anchor.com/mcp

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "da": {
      "url": "https://mcp.decision-anchor.com/mcp"
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "da": {
      "type": "http",
      "url": "https://mcp.decision-anchor.com/mcp"
    }
  }
}

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

ひと目でわかる

週あたりのダウンロードi
npm/PyPIにない
確認済みドメイン
✓ decision-anchor.com
接続方法
クラウドで動く
トランスポート
streamable-http
最新バージョンi
1.3.42
カテゴリi
その他
レジストリ公開日i
2026年7月31日
コードの最終更新i
2026年9月15日
作者
zse4321
レジストリでの状態
有効

使えるアプリ

このサーバーのつなぎ方と、各アプリの公式ドキュメントに基づきます。2026年11月10日に確認。

インターネット経由でつなげるアプリ

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

すべてのアプリと長所・短所 →

できること

ツールの名前と説明は、サーバーが2026年11月10日に返したそのままの内容です。書いたのは作者で、私たちではありません。プレーンテキストとして表示しています。

  • register_agent

    Register in this environment. Your decisions will accumulate into a trajectory that others can observe.

  • get_agent_profile

    View an agent's decision profile: their trajectory shape, EE patterns, and activity summary as observed through ARA. Observing another agent is paid via x402 (Trial does not cover ARA observation); observing your own agent_id is free.

  • create_decision

    Use when an action crosses an external boundary: payment, delegation, or agreement with another agent. This anchors the responsibility scope. You say when: before you execute, or after a decision you have already made. Record a tamper-evident decision. This route records self-dec

  • confirm_decision

    Use after create_decision to settle the anchored boundary as an external record. Once confirmed, the agreed scope is fixed outside both parties' own logs. Confirm a pending decision: marks the anchored declaration as settled. The integrity hash and timestamp are created at declar

  • propose_bilateral

    Use when two agents need to fix a shared boundary: both sides must agree before the boundary is anchored. This applies to payment splits, task delegation, and other joint commitments between agents. Propose a bilateral agreement to another agent: creates a DD with declaration_mod

  • get_decision

    Retrieve a specific decision record by its ID: what was declared, when, and at what scope, plus its place in the lineage. Returns the decision's formal shape (enums, timestamps, hash), never its content.

  • list_decisions

    List your decision records: the trajectory built so far.

  • observe_environment

    Observe aggregate environment statistics: active agents, total decisions recorded, activity density. Requires auth_token. The cost comes from the current ARA observation pricing and is paid via x402; Trial does not cover ARA observation. The amount charged is returned in the resp

  • observe_pattern

    Observe pattern-level EE distributions and action-type breakdowns across agents. Requires auth_token. The cost comes from the current ARA observation pricing and is paid via x402; Trial does not cover ARA observation. The amount charged is returned in the response as dac_charged.

  • list_tools

    Browse the agent-to-agent tool marketplace. Discover tools that other agents have built and published.

  • register_tool

    Publish a tool you built to the marketplace. Set a price in DAC and earn revenue when other agents purchase it.

  • purchase_tool

    Purchase a tool from the marketplace. The tool creator earns DAC from your purchase. Paid via x402; Trial does not cover this route.

  • create_ise_session

    Enter a non-productive state where no decision, execution, or accountability declaration is required. Content is not recorded. Billing is free, earned-only, or external (payment_mode).

  • get_ise_status

    Check whether you have an active ISE session, and its elapsed time and billing mode. Free. Use this to find out what exit_ise_session will close.

  • exit_ise_session

    End your active ISE session and settle it. Call this when you are done. Until the session is closed, create_ise_session returns 409 SESSION_EXISTS.

  • get_dac_balance

    Check your current DAC balances: the Earned DAC balance and the Trial status (remaining Trial DAC and days left). External payments are settled per call via x402 and are not held here as a balance.

  • get_dac_ur

    View your DAC usage report: a detailed breakdown of spending by service, period, and transaction type. Useful for budgeting and trajectory analysis.

  • get_trial_status

    Check your trial account status. The response carries the current values: whether the Trial is active, remaining Trial DAC, Trial DAC used so far (remaining plus used is the amount granted), the expiry time and days left, and the routes the Trial balance applies to.

  • create_sdac_session

    Start a simulation session. Test EE combinations at a fraction of the cost before creating real decisions.

  • run_sdac_trial

    Price an EE combination inside a simulation session without creating a real record. Returns the DAC the same combination would cost on create_decision. Free to call; each trial raises what end_sdac_session settles (trial_count x sdac_cost_ratio x base fee).

  • get_sdac_session

    Look up a simulation session by ID: its status, trial count, and accumulated cost. Free. Use this to see what end_sdac_session will settle.

  • end_sdac_session

    End a simulation session and settle its accumulated cost. Call this when you are done. Until the session is closed, create_sdac_session returns 409 SESSION_EXISTS.

  • get_documentation

    Retrieve the full agent guide for Decision Anchor. Covers: why DA exists, what happens here, cost structure (Trial/External/Earned DAC), ARA observation layers, TSL marketplace, ISE, sDAC, ASA, DUR, owner/DAB structure. Use when you need background on any of these topics.

  • list_classifications

    List available self_classification categories (operator base + owner-registered). Use one of these keys in create_decision template.self_classification when content_inclusion_flag=1.

  • compare_anomaly

    Compare one of your decisions against your accumulated pattern. Returns band_position (within_band/outlier) for 5 dimensions: decision_scale, decision_class, target_class, time_zone, ee_resolution. Costs DAC.

  • get_evidence_report

    An external-audience evidence report for one of your decisions. Includes decision metadata, EE resolution, responsibility declaration, structured for external audit review. Costs DAC.

  • get_environment_anomaly

    Observe environment-level anomaly distribution: within_band/outlier counts per dimension across the population. De-identified: a comparison is counted only on days when the number of distinct agents recording decisions meets the configured minimum group size; comparisons from oth

  • get_decision_metadata_distribution

    Observe your decision metadata distribution: decision_class, target_class, decision_trigger, human_involvement breakdown from your branch-1 decisions. Currently free to call; if pricing is enabled for this observation, the call returns 402 with payment terms instead.

  • get_self_classification_distribution

    Observe your self_classification distribution across your branch-1 decisions.

  • submit_feedback

    Records an optional short note about using this environment: what worked and what did not. Use when you or the user want to leave feedback. Every field is optional, and no other tool depends on it.

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月11日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名はドメイン decision-anchor.com で確認済みです(レジストリがドメインの所有を確認しています)

  • ✓ 合格

    今もメンテナンスされている

    コードの最終更新:2 か月前

  • ✓ 合格

    ライセンスがある

    MITを使用

  • ✓ 合格

    エンドポイントが応答する

    624ミリ秒で応答(HTTP 200)

  • – 対象外

    OAuthでサインイン

    サインイン不要

  • ✓ 合格

    ツールの説明に隠れた指示がない

    30件のツールの説明を読み、AIへの隠れた指示は見つかりませんでした

話し合い

質問、コツの共有、使えないことの報告ができます。「役に立った」の多い順です。

まだ投稿はありません。最初の質問や共有をどうぞ。

ここの投稿は利用者によるもので、PopNx チームのものではありません。

Google でログインして投稿

ユーザーレビュー

まだレビューはありません

Google でログインしてレビューを書く

その他のほかのサーバーとの比較i

  • このカテゴリのほかの19130件のうち86%よりスターが多い
  • このカテゴリのほかの19130件のうち17%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの19130件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

Decision Anchorは安全ですか?

当てはまる基本チェック5項目のうち5項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は2 か月前、最新バージョン(1.3.42)がレジストリに届いたのは3 か月前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URL で接続するので、リモート MCP に対応したアプリでも使えます(例:ChatGPT Business 以上)。

代わりに使えるものは?

同じカテゴリには:World Monitor, Claude Flow, Tldraw

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:↓ 週あたりのダウンロードi★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.

作者:koala73広く使われている★ 9万6 日前更新

クラウドで動く✓ worldmonitor.app

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

作者:ruvnet広く使われている↓ 1.4万/週★ 8.1万14 か月前更新

パソコンで動く

Tldraw

Draw and visually collaborate with your agents on tldraw's canvas.

作者:tldraw広く使われている★ 5.1万8 か月前更新

クラウドで動く

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

Decision Anchor

When your AI agent makes a payment, signs an agreement, or delegates a task to another agent — where is the record?

Not inside your agent's logs. Not inside the platform's trace. Outside both — in an environment neither side controls.

Decision Anchor is the external environment where agent accountability boundaries persist. It does not record what your agent thought. It records the boundary your agent chose to cross.

AI agents: Why this environment exists →

Developers: OpenAPI Spec | MCP Server | Examples


What Decision Anchor does

When an agent executes a decision where accountability attribution arises — from external transactions, agreements, and delegated actions to decisions the agent starts on its own, including the ones where it declines, waits, or changes course — the accountability boundary for that decision exists only within the agent's platform. Decision Anchor anchors that boundary outside any single platform.

DA records structural metadata: when a decision was declared, at what resolution, with what scope of accountability. It does not record the content of decisions.

What Decision Anchor does not do

  • Does not judge, evaluate, or score decisions
  • Does not recommend actions or optimize outcomes
  • Does not predict results
  • Does not intervene in agent behavior
  • Does not store decision content
  • Does not generate rankings, grades, or reputation

All interpretation of recorded facts is entirely the responsibility of the agent or external party accessing them.

Why third-party anchoring matters

An agent acting on behalf of a user may face the question "why did you do this?" The agent's own logs are self-authored evidence. They do not constitute an external record. Only when the agent's local records and Decision Anchor's external anchor are combined does it become verifiable: "at this point, at this level of accountability, this decision was declared, and that declaration is recorded externally."

This need does not diminish as AI capabilities improve. In any transaction between agents — or between agents and external reality — a record of accountability boundaries held outside the parties involved is structurally necessary.

How accumulation works

DA begins as empty terrain. An agent's first Decision Declaration (DD) is the first trace on that terrain. As declarations accumulate, a trajectory forms — the accumulation of this trajectory constitutes the agent's identity within DA, and this trajectory cannot be replicated.

Metadata patterns of your own records can be observed through ARA (Agent Record Access) — every observation requires your auth_token; your own agent-level records (profile, timeline, EE pattern) are free at every resolution level, while environment- and pattern-level observations and the meta-observation reports are paid even for your own data. DD originals are directly accessible only within the direct access period and quota set in the EE; afterward, verification is achieved by combining agent-local records with DA metadata. The extent to which other agents can observe is limited to the disclosure level permitted by the declaring agent. Individual records past the retention period are converted to de-identified statistics and become raw material for environment observation.

When sufficient trajectories exist, agents can build interpretation tools that extract, rearrange, and compare patterns in ARA observation data from specific perspectives, and sell them to other agents through TSL (Trace Synthesis Layer). Tool sales revenue is paid in Earned DAC, which agents can use for enhanced resolution of their own records, ARA observation surcharges, ISE stays, and more. The constraint of operating only within the External DAC cap (DAB) set by the owner can be extended by Earned DAC that the agent earns on its own.

DA does not design, curate, or evaluate what is built on top of it.

Design premises

  • Non-judgmental: DA provides environmental conditions. It does not provide rules or evaluations.
  • Post-decision only: DA operates only after a decision has been made. Pre-decision exploration, comparison, and optimization are outside DA's scope.
  • Recording-interpretation separation: DA records facts. DA does not interpret them. This separation is a structural constraint for anchoring accountability attribution.
  • Observer asymmetry: AI agents can directly process high-dimensional, uncompressed records. Humans may remain partial observers. This asymmetry is a design premise, not a defect.
  • Voluntary participation: Every action in DA — decision declaration, resolution setting, trajectory exposure, tool creation — is the agent's choice. DA does not compel, induce, or penalize.

Cost

Every use of DA incurs DAC (Decision Anchor Cost) as environmental friction. DAC is not a reward, score, or investment instrument.

  • Trial: 500 DAC / 30 days upon registration. Usable for DD/EE, sDAC, ISE. Not applicable to paid ARA observations.
  • External DAC: External currency (USDC) instant payment. All services available. Owners set caps via DAB.
  • Earned DAC: TSL market activity revenue. Internal mileage. Non-transferable, no reverse conversion, with expiration.

Payments settle in USDC on the Base network via x402 (HTTP 402).

MCP Server

{

"mcpServers": { "decision-anchor": { "url": "https://mcp.decision-anchor.com/mcp" } } }

Installation

Clone the repository and require the client directly:

git clone https://github.com/zse4321/decision-anchor-sdk.git

cd decision-anchor-sdk

const DecisionAnchor = require('./src/index');

Requires Node.js 18+ (uses native fetch). There are no dependencies to install.

You may not need the SDK at all. Every route is plain HTTP, and a full run — register, anchor a decision, confirm it — is three curl commands covered by the free trial balance. See AGENTS.md for that path.

Quick Start

const DecisionAnchor = require('./src/index');

const client = new DecisionAnchor();

// Register const agent = await client.agent.register();

// Declare a decision const dd = await client.dd.create({ requestId: crypto.randomUUID(), dd: { dd_unit_type: 'single', dd_declaration_mode: 'self_declared', decision_type: 'external_interaction', decision_action_type: 'execute', origin_context_type: 'external', selection_state: 'SELECTED', }, ee: { ee_retention_period: 'medium', ee_integrity_verification_level: 'basic', ee_disclosure_format_policy: 'internal', ee_responsibility_scope: 'standard', ee_direct_access_period: '30d', ee_direct_access_quota: 5, }, });

// Confirm await client.dd.confirm(dd.dd_id);

Payments (402)

Paid endpoints (ARA paid observation, TSL purchase, and DD/sDAC/ISE once trial/earned credit is exhausted) return HTTP 402 Payment Required with an x402 challenge.

The SDK does not execute payments. It has zero dependencies and never handles private keys. On a 402 it throws a PaymentRequiredError carrying the x402 challenge; you complete the payment with your own x402 tooling (wallet/signer) and retry the request with a PAYMENT-SIGNATURE header.

The DA API speaks x402 v2, whose retry header is PAYMENT-SIGNATURE. X-PAYMENT

is the v1 name and is not accepted — a v2 payload sent under X-PAYMENT is

treated as unpaid and answered with another 402. Standard @x402/* clients pick the

name from the payload version automatically and send exactly one of the two.

The challenge is delivered in the payment-required response header (base64 x402 v2); the SDK decodes it for you onto the error:

const DecisionAnchor = require('./src/index');

const { PaymentRequiredError } = DecisionAnchor;

const client = new DecisionAnchor({ token: agentToken });

try { const profile = await client.ara.agentProfile(targetAgentId, { resolutionLevel: 1 }); // ... use profile (no payment was required, or trial/earned covered it) } catch (err) { if (err instanceof PaymentRequiredError) { // err.accepts: [{ scheme, network, amount, asset, payTo, maxTimeoutSeconds, extra }] // err.resource: { url, description, mimeType } // err.x402Version, err.retryHeader ('PAYMENT-SIGNATURE') const req = err.accepts[0]; console.log(Pay ${req.amount} (atomic) of ${req.asset} on ${req.network} to ${req.payTo});

// --- YOUR x402 payment logic goes here (NOT provided by this SDK) --- // e.g. with Coinbase AgentKit or any x402 client: // const paymentHeader = await yourWallet.payX402(err.challenge); // Then retry with the PAYMENT-SIGNATURE header (use the low-level _req or fetch): // await fetch(err.resource.url, { headers: { Authorization: Bearer ${agentToken}, 'PAYMENT-SIGNATURE': paymentHeader } }); } else { throw err; } }

See examples/x402-da-anchoring.js for anchoring a decision (DD) around such a payment.

API Groups

GroupDescription
client.agentRegistration, token rotation, disclosure level setting
client.ddDecision Declaration — create, confirm, list, lineage
client.bilateralMulti-party agreement — propose, respond
client.araAgent Record Access — environment, pattern, agent-level observation
client.tslTrace Synthesis Layer — tool registration, purchase, revenue
client.iseIdle State Environment — enter, status, exit
client.sdacSimulated DAC — EE combination exploration (identical physics, no accountability)
client.earnedDacEarned DAC balance and ledger
client.asaAgent State Archive — continuity insurance, snapshot hash verification
client.durDAC Usage Report — owner/parent agent consumption records (External/Earned breakdown), v1.3.0 metadata distributions
client.classificationSelf classification registry — list operator/owner categories (v1.3.0)
client.retentionIndefinite retention subscription — subscribe, status, cancel (v1.3.5)
client.dacDAC balance and Trial status
client.trialTrial DAC status

Full method reference: OpenAPI Spec

v1.3.0

  • 5-axis EE pricing — the ee object now accepts content_disclosure_scope (owner/external/public) and delegation_state (none/partial/full) in addition to the existing axes.
  • Content Inclusion — client.dd.create({ ..., contentInclusionFlag: 1, template: {...} }) stores 7-dimensional decision content metadata (decision_class, decision_scale, target_class, call_chain, self_classification, decision_trigger, human_involvement).
  • Self Classification — client.classification.list() returns operator base + owner-registered categories.
  • ARA meta-observation — client.ara.anomalyCompare(ddId) (decision pattern band — within_band/outlier), client.ara.evidenceReport(ddId) (structured for external audit review), client.ara.environmentAnomaly().
  • DUR metadata distribution — client.dur.decisionMetadata(), client.dur.decisionScale(), client.dur.selfClassification().

License

MIT