Recomend
Recomend's pricing page did not render numeric tier data on the scoring date. No per-unit price was found on the page; an agent has no direct way to estimate the cost of a single task. Public API documentation is reachable without an auth wall.
Recomend pricing
We’re still verifying Recomend’s pricing
The provided body text describes a gambling platform (Lixi88) unrelated to the Recomend product, and contains no SaaS pricing information. Consequently, pricing fields are left null or defaulted, and the model is marked as unverified.
Source of truth: recomend.io/pricing/
How Recomend scores on the agent-ready dimensions
Public pricing
0 / 15
Usage-based / metered
0 / 25
Self-serve checkout
0 / 15
Public API
15 / 15
Low / no minimum
0 / 10
Unauth automated payment
0 / 10
Bonus (machine-readable pricing)On top of /100 base
0 / 5
Total
15 / 100
Six-step check: can an agent actually buy from Recomend?
Discover price
Select a plan
Pay per task
Avoid a sales call
API docs without auth
Estimate cost upfront
Pros and cons for AI agents
Observational summary written by xpay from the signals captured on 2026-05-06. Not a review of the product — only of its current pricing posture for agent buyers.- Pricing is publicly visible on an indexable page — agents can read tiers without scraping past auth.
- Every advertised tier is self-serve; no tier requires scheduling a call.
- No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
- API documentation is gated or absent; an agent cannot inspect the integration surface without authentication.
- No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
- The pricing URL did not render numeric tier data on the scoring date — possibly a router or sales-led landing page.
How Recomend could lift its score
Add a per-unit price (e.g. $X / 1K calls) to the pricing page so an agent can compute its own cost before committing.
| pricing_visible | false |
| headline_phrasing | Lixi88 – Thế Giới Giải Trí Đỉnh Cao Mùa Tết Bính Ngọ 2026 — Xổ số siêu tốc là một kiểu chơi đánh đề còn rất mới mẻ ở Việt Nam. Ưu… |
| tier_count | 0 |
| lowest_paid_entry_usd | null |
| free_tier | false |
| free_tier_terms | null |
| per_unit_price | null |
| annual_required | false |
| self_serve_paid_tiers | 0 |
| sales_only_tiers | 0 |
| public_api_docs_url | https://gerhik-online.in.net/ |
| api_docs_auth_walled | false |
| ai_pricing_json_present | false |
| agents_txt_present | false |
| anonymous_purchase_path | false |
| per_unit_classification | null |
| usage_headline_present | false |
| custom_tier_present | false |
| agent_friendly | {"ai_pricing_json":false,"agents_txt":false,"llms_txt":false,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false} |
View raw extracted page text →
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See agent-ready picksRecomend
15
/ 100 (rubric v1.1)Reputation Management
Not advertised
0
No
Sales-led
0 / 0
Public
No
Not published
2026-05-06
Discovery files and protocols
Side-channel signals — informational, not part of the score. Each protocol is independent; adoption signals the publisher is thinking about agent buyers.ai-pricing.json
agents.txt
llms.txt
sitemap.xml
MCP Server Card
Agent Skills
x402 / MPP
Compare Recomend with peers
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Endorsal
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Explore the Agent-Ready SaaS Index
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