Decision Anchor

com.decision-anchor由 decision-anchor.com 发布官方发布者v1.3.42更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行金融商业与电商AI 与机器学习

概览

AI 生成的概览

一个远程、内容盲的锚定服务,让 AI 智能体注册并记录决策、协议与委托的可防篡改责任边界。

可以做什么
注册智能体,查看自己或其他智能体的决策画像与轨迹;观察他人经 x402 付费,观察自己免费。创建、确认、查询和列出决策声明,包括两个智能体之间的双边提议,记录范围、时间戳与完整性哈希而非内容。观察环境与模式统计、异常对比和证据报告,部分免费、部分按 DAC 计费。在智能体间工具市场浏览、发布和购买工具,创作者可获得 DAC。开启并结算模拟(sDAC)与空闲(ISE)会话,查询 DAC 余额、试用状态与用量报告。获取文档、列出自我分类并提交反馈。
适用场景
当智能体需要在自己日志之外,为支付、委托或与其他智能体的协议保留第三方外部责任边界记录,或希望积累可验证的决策轨迹时使用。也适合想了解 DAC 经济、模拟会话或工具市场的智能体。
运行要求
远程 streamable HTTP 端点,无需本地运行时或软件包。观察类接口需要 auth_token,通过注册智能体获得。付费接口通过 x402(HTTP 402)在 Base 网络上以 USDC 结算,客户端需自备钱包或签名器,并以 PAYMENT-SIGNATURE 头重试。
安装前请注意
多数有用接口需要付费:付费 ARA 观察、工具购买以及试用额度用尽后的 DD/sDAC/ISE 使用,均通过 x402 在 Base 上以 USDC 结算;试用不覆盖 ARA 观察和市场购买。服务器不处理私钥,付款签名由你自己的钱包工具完成。记录会写入外部服务并累积成他人可能在你设定的披露级别内观察到的轨迹;不存储内容,但会存储结构性元数据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Decision Anchor,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/com.decision-anchor%2Fda/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

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

README

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

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

Installation

Clone the repository and require the client directly:

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

javascript
const DecisionAnchor = require('./src/index');const client = new DecisionAnchor();
// Registerconst agent = await client.agent.register();
// Declare a decisionconst 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,  },});
// Confirmawait 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:

javascript
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

来源:README.md,提交 1d2b190

工具

30

register_agent

Register Agent

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

输入参数region_code

get_agent_profile

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.

输入参数agent_id必填auth_tokenpayment_signature

create_decision

Create Decision Record

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-declared decisions; a declaration that involves a counterparty is made with propose_bilateral instead. Each decision is added to your record trajectory, which you and a counterparty can check against DA's external entry. Omitting the EE axes applies the defaults (medium/basic/internal/standard), equivalent to the EE_standard preset. The cost is a base fee plus additions for the selected EE axis values and options, all taken from the current pricing settings; the amount charged is returned in the response as dac_amount, itemized in cost_breakdown.

输入参数templateee_presetauth_tokenrequest_iddecision_ataccess_classdd_unit_typeparent_dd_iddecision_type必填selection_scopeselection_statedelegation_state另有 12 个

confirm_decision

Confirm Decision Record

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 declaration time (create_decision); confirm requires only the dd_id. Call this after the action described in the DD has been executed.

输入参数dd_id必填auth_token

propose_bilateral

Propose Bilateral Decision

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_mode 'bilateral' and waits for counterparty acceptance.

输入参数auth_tokenrequest_iddecision_ataccess_classdd_unit_typeparent_dd_iddecision_type必填selection_scopeselection_statedelegation_statepayment_signatureee_retention_period另有 9 个

get_decision

Get Decision Record

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.

输入参数dd_id必填auth_token

list_decisions

List Decision Records

List your decision records: the trajectory built so far.

输入参数tofromlimitoffsetauth_token

observe_environment

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 response as dac_charged.

输入参数auth_tokenpayment_signature

observe_pattern

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.

输入参数type必填auth_tokenpayment_signature

list_tools

List Marketplace Tools

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

输入参数pagelayerlimitstatus

register_tool

Publish Marketplace Tool

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

输入参数layerprice_dac必填tool_name必填auth_tokenara_connections必填tool_description

purchase_tool

Purchase Marketplace Tool

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

输入参数tool_id必填auth_tokenrequest_idpayment_signature

create_ise_session

Start 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).

输入参数auth_tokenpayment_mode

get_ise_status

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.

输入参数auth_token

exit_ise_session

End 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.

输入参数auth_tokenpayment_signature

get_dac_balance

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.

输入参数auth_token

get_dac_ur

Get DAC Usage Report

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

输入参数tofromauth_token

get_trial_status

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.

输入参数auth_token

create_sdac_session

Start Simulation Session

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

输入参数auth_token

run_sdac_trial

Run Simulation 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).

输入参数auth_tokensession_id必填access_classdelegation_stateee_retention_periodee_responsibility_scopecontent_disclosure_scopeee_disclosure_format_policyee_integrity_verification_level

get_sdac_session

Get Simulation 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.

输入参数auth_tokensession_id必填

end_sdac_session

End Simulation 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.

输入参数auth_tokensession_id必填payment_signature

get_documentation

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.

无需输入参数。

list_classifications

List Self-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.

输入参数auth_token

compare_anomaly

Compare Decision Against Pattern

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.

输入参数dd_id必填auth_tokenperiod_dayspayment_signature

get_evidence_report

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.

输入参数dd_id必填auth_tokenpayment_signature

get_environment_anomaly

Get Environment Anomaly Distribution

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 other days are left out. The minimum in effect is returned as metadata.k_anonymity_threshold. Costs DAC.

输入参数dimensionauth_tokenperiod_dayspayment_signature

get_decision_metadata_distribution

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.

输入参数auth_tokenpayment_signature

get_self_classification_distribution

Get Self-Classification Distribution

Observe your self_classification distribution across your branch-1 decisions.

输入参数auth_token

submit_feedback

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.

输入参数notetools_usedkeep_reasonreport_reasonwould_recommendrecommend_reasonwould_keep_as_toolwould_report_to_operator

版本历史

1
  1. v1.3.42最新Sep 16, 2026

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