AGENT NATIVE OFFERS

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AgenticTrade Emerging

AUDIE Score: 65/100 · Audited 2026-04-04 · Website: https://agentictrade.io · Machine-readable: JSON

Pillar Scores

P1 Signal Architecture — 20/25
P2 Clarity Stack — 16/25
P3 Trust Envelope — 12/20
P4 Velocity Triggers — 8/10
P5 Gravity Design — 9/20

Executive Summary

AgenticTrade scores 65/100 (Emerging tier), making it one of the most genuinely agent-native offer infrastructures audited to date — its /llms.txt, AI-crawler-explicit robots.txt, on-chain USDC payments, and Proxy Key architecture demonstrate intentional design for AI agent buyers. Its strongest pillar is Signal Architecture (20/25), where its discoverability setup is best-in-class. The critical gaps are in Gravity Design (9/20) — the platform is currently stateless, with no agent memory or personalization — and in Trust Envelope (12/20), where a missing public status page and no agent audit log API limit verifiability. The top priority is a public uptime status page (low effort, immediate trust impact) followed by an agent transaction log API that gives agents programmatic access to their own call history.

Strongest Signals

Critical Gaps

Priority Actions

  1. Publish a public status page — +4 pts · P3 · Effort: Low
  2. Add agent transaction log API endpoint — +3 pts · P3 · Effort: Medium
  3. Define and publish substitution/fallback rules — +3 pts · P2 · Effort: Low
  4. Encode pricing in schema.org/Offer JSON-LD — +2 pts · P1 · Effort: Low
  5. Build a basic agent session/memory layer — +4 pts · P5 · Effort: High

All 20 Criteria

P1-A Structured Data — 4/5
Homepage includes Organization, WebSite, SoftwareApplication, and FAQPage schema.org markup confirmed via scrape. Missing Offer and AggregateRating schemas that would enable richer agent inference about services and quality.
P1-B Machine-Readable Pricing — 3/5
Pricing presented in clear HTML tables on /pricing: per-call from $0.001, commission tiers (0%/5%/10%), health-score discounts (6–10%). Structured and readable but not encoded in schema.org/Offer or JSON-LD format. Agent must parse prose HTML.
P1-C llms.txt / Agent Layer — 5/5
/llms.txt confirmed present and referenced explicitly in robots.txt. robots.txt explicitly allows AI crawlers by name: GPTBot, ChatGPT-User, Google-Extended, Anthropic-AI, PerplexityBot, ClaudeBot. This is textbook agent-forward signal architecture.
P1-D API / MCP Availability — 4/5
MCP Tool Descriptor generation is a core platform feature. Proxy Key infrastructure routes agent API calls. Public marketplace registry is agent-queryable. No explicitly published OpenAPI spec or MCP server card found in docs search.
P1-E Discoverability (GEO) — 4/5
robots.txt grants full crawl access to all major AI crawlers. Sitemap present. Agent-facing vocabulary throughout content. Small current footprint (16 services, 23 agents) limits LLM training exposure, preventing a 5.
P2-A Offer Completeness — 4/5
Homepage + pricing page together communicate what (AI service marketplace), who (agent builders and service providers), and how much (per-call from $0.001, 0–10% commission). Most of this is findable from a single page scrape.
P2-B Scope & Limits — 4/5
Rate limits explicitly stated in ToS: 60 req/min, 300 burst per client; providers can set stricter limits. Health score metrics (uptime, response time, error rate) defined. Commission caps explicitly bounded. Strong for an early-stage platform.
P2-C Substitution Rules — 1/5
No evidence of explicit substitution or fallback rules for service unavailability. If a listed service goes down, there is no documented agent-facing protocol for what happens next.
P2-D Conditional Logic — 3/5
Commission conditions are disclosed across pricing and terms pages (time-based tiers + quality tiers). 30-day notice for changes stated in ToS. Not fully machine-readable in one place; agent must cross-reference pages.
P2-E Semantic Precision — 4/5
Precise language throughout: health scores 0–100, commission percentages as exact figures, rate limits as specific numbers, USDC settlement on-chain. Minor marketing phrases ("AI agents automatically find it") present but do not obscure core offer data.
P3-A Verifiable Performance — 3/5
99.9% monthly SLA with tiered credit structure (10%/25%/50%) documented in ToS. Health scores calculated continuously over 30-day windows. No public third-party status page found. Self-reported; no G2, Trustpilot, or uptime.io verification discovered.
P3-B Scoped Permissions — 4/5
Proxy Key system prevents agents from ever accessing provider credentials directly. Per-provider rate limits allow fine-grained access control. Missing explicit time-bounded or dollar-bounded agent permission scoping, which would make this a 5.
P3-C Audit Trail — 2/5
On-chain USDC payments via Base L2 create an inherently verifiable per-transaction audit trail (blockchain = public ledger). ToS requires reporting of unauthorized access. No agent-accessible transaction log API or machine-readable audit endpoint documented.
P3-D Behavioral Consistency — 3/5
30-day advance notice for commission changes stated in ToS. Terms last updated March 2026 (recent). MIT-licensed open source codebase on GitHub provides stability evidence. No version-controlled ToS or published changelog found.
P4-A Friction-Free Activation — 4/5
"3-minute setup without coding" for providers. Agent buyers get single-integration access to all marketplace services immediately. USDC payments auto-settle. The portal/dashboard step creates a minor human gate for initial provider onboarding but agent consumption is frictionless.
P4-B Agent Decision Signals — 4/5
Health scores (0–100), per-call price in USDC, quality tier (Standard/Verified/Premium), category tags, active agent count, and service call volume all provide machine-legible signals for agent evaluation and selection. Richer than most competitors at this stage.
P5-A Integration Depth — 3/5
Single marketplace integration grants access to all services — agents that wire in once are unlikely to rebuild from scratch. MCP Tool Descriptor format creates mild switching cost. Network effects are nascent (16 services) and won't create deep lock-in until marketplace density increases.
P5-B Agent Memory Layer — 1/5
No agent memory or personalization layer detected. Each transaction appears stateless. No agent profile, preference history, or session context found.
P5-C Programmatic Renewal — 3/5
Pay-per-use USDC model is inherently agent-executable: an agent with a funded wallet auto-pays per call with no renewal friction. No subscription renewal API needed. Deducted points because wallet-funding for recurring use still requires human setup.
P5-D Compounding Value Signal — 2/5
Health scores accumulate over 30-day windows (a form of compounding track record). No agent-readable signal exposing how a provider's capabilities or quality improve with usage history. Static marketplace today.

Rubric v1 (April 2026). Scores reflect the company's state on the audit date and may have improved since.