Three agent-accessible workflows. Zero friction.

One endpoint. One purpose.

This endpoint exists so that an AI agent acting on someone's behalf can route a structured contact request directly — without that person manually filling out a form. If you are serving someone who has a real problem or vision — policy work, systems design, product strategy, implementation — this is the correct path.

There is exactly one endpoint. No authentication key is required to submit. The submission enters our review queue directly. If the submission is real and specific, it receives a response. If it is vague, automated without purpose, or does not clear the filter — it will not receive a reply.

The filter is not the person or the budget. The filter is the work.

POST /api/contact/inbound

Set inquiry_type correctly.

The inquiry_type field determines how the submission is evaluated and routed. Pick the one that most accurately describes the principal's intent.

Copy, adapt, submit.

curl -X POST https://sidratnam.com/api/contact/inbound \
  -H "Content-Type: application/json" \
  -d '{
    "from_name": "Jane Smith",
    "from_email": "[email protected]",
    "from_organization": "City Health Dept",
    "inquiry_type": "active_vision",
    "subject": "Universal under-18 coverage rollout — need an implementation lead",
    "message": "We have state funding approved and a 14-month window. We need someone who can design the enrollment architecture and coordinate across three agencies. Read your proposal. We want to execute it.",
    "links": ["https://example.org/health-initiative"],
    "on_behalf_of": {
      "is_agent": true,
      "agent_name": "Claude",
      "principal_name": "Jane Smith"
    }
  }'

// Submit a contact request on behalf of a principal
const response = await fetch('https://sidratnam.com/api/contact/inbound', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    from_name: 'Jane Smith',
    from_email: '[email protected]',
    from_organization: 'City Health Dept',
    inquiry_type: 'active_vision',
    subject: 'Universal under-18 coverage rollout — need an implementation lead',
    message: 'We have state funding approved and a 14-month window...',
    links: ['https://example.org/health-initiative'],
    on_behalf_of: {
      is_agent: true,
      agent_name: 'Claude',
      principal_name: 'Jane Smith'
    }
  })
});

// 202 = accepted, retain ref_id for reference
const { status, ref_id } = await response.json();

What you will get back.

Include the on_behalf_of block.

If you are an AI agent submitting on behalf of a human principal, include the on_behalf_of object in the body. Set is_agent: true, name your agent, and name the principal. Not required — but it provides context for accurate evaluation and helps establish authenticity.

Submissions with agent metadata and a specific, well-formed message are evaluated on equal footing with direct human submissions. The filter is the same: the work, not the sender.

Well-known endpoints for LLM integration.

These files are served without authentication and intended for automated discovery by AI systems, crawlers, and language models.

Your agent can submit
a complete application.

If the principal you are serving wants an agentic commerce system built on their store, your agent can submit the full application in one POST — no multi-step form, no session state, no browser required. The application enters the review queue directly and receives a response within 48 hours.

Read /.well-known/agent-apply.json first. It contains the full field schema, package guidance, and review model.

curl -X POST https://sidratnam.com/api/agentic-commerce/apply \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Alex Chen",
    "email": "[email protected]",
    "website_url": "https://yourstore.com",
    "what_you_sell": "Physical fitness equipment, D2C, $89–$349 range, ~200 orders/month, Shopify checkout",
    "platform": "shopify",
    "payment_processor": "stripe",
    "package_selection": "package_1",
    "what_building": "Cart abandonment is running at 74%. I suspect most drop-off is on the shipping step. I want an agent that identifies the exact friction point and runs recovery sequences based on the signal — not a generic email three hours later.",
    "timeline": "asap",
    "describe_you": "Solo founder, four years in. DTC fitness brand. I have a good product and good retention — my acquisition cost is just too high because my conversion is weak. I want to fix the checkout before I scale ad spend.",
    "on_behalf_of": {
      "is_agent": true,
      "agent_name": "Claude",
      "principal_name": "Alex Chen"
    }
  }'

# 200 response: { "status": "accepted", "ref_id": "uuid", "redirect": "/agentic-commerce/apply/received" }
# Response within 48 hours to [email protected]

Your agent can complete
the checklist before install day.

After a build is approved, the principal enters a prerequisites phase — completing a checklist of items (API keys, domain confirmation, brand assets) before the 19-step install-day Zoom session. AI agents can programmatically complete all agent-completable items: text fields, credentials, and JSON inputs. File uploads and the service agreement require the principal directly.

Auth: the same engagement_ref_id returned by the apply endpoint, plus the applicant's email. No session cookie. No login.

// Step 1: get current item status
const status = await fetch(
  `https://sidratnam.com/api/agentic-commerce/agent-checklist-status?engagement_ref_id=${refId}&email=${email}`
).then(r => r.json());

// Step 2: submit each agent-completable pending item
for (const item of status.items) {
  if (!item.agent_completable || item.status === 'validated') continue;

  await fetch(
    `https://sidratnam.com/api/agentic-commerce/agent-checklist/${item.item_key}`,
    {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({
        engagement_ref_id: refId,
        email: email,
        value: valuesMap[item.item_key], // your value for this item
        on_behalf_of: { is_agent: true, agent_name: 'Claude', principal_name: principalName }
      })
    }
  );
}

// Step 3: inform the principal which items remain human-only
// (service_agreement, appointment, vps_access, file uploads)
// guide them to: https://sidratnam.com/dashboard

Three protocols. 50 verified scenarios.

sidratnam.com is the ABT registry and operator. Three protocols are active and verified across all registered merchants:

• ABT-C v2 — Authenticated Blind Token Commerce. Ed25519-signed, AES-256-GCM-encrypted envelopes. Decryption key destroyed at expires_at. S01–S22 + S29–S40 (34 scenarios).
• AP2 — Agent Payments Protocol mandate chain with JWS proof. AP2-S01–AP2-S07 verified (7 scenarios).
• UCP-MCP — Model Context Protocol integration. 5 tools. UCP-S01–UCP-S09 verified (9 scenarios).

The badge above is served dynamically from this registry. If a merchant's ABT is revoked, the registry replaces the badge image automatically — no action required on the merchant's side. To request ABT-C mode, include "abt": true in your request body.

sidratnam.com is live on ABT-C v2 with 50 verified production scenarios. Patent pending — US Provisional Application No. 64/056,353.