R2DTools
R2DTools'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. No public API documentation URL was discovered.
R2DTools pricing
We’re still verifying R2DTools’s pricing
The page contains extensive content about slot machine strategies but provides no pricing, plan, or purchase information for R2DTools. Consequently, most pricing-related fields are null and the model is classified as unverified.
Source of truth: r2dtools.com/
How R2DTools scores on the agent-ready dimensions
Public pricing
0 / 15
Usage-based / metered
0 / 25
Self-serve checkout
0 / 15
Public API
0 / 15
Low / no minimum
0 / 10
Unauth automated payment
0 / 10
Bonus (machine-readable pricing)On top of /100 base
0 / 5
Total
0 / 100
Six-step check: can an agent actually buy from R2DTools?
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.
- No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
- All advertised tiers route to a sales contact form; an agent cannot complete a purchase autonomously.
- 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 R2DTools 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 | SEO PROMAX – R2dtools — Slot online terpercya kini memasuki era baru dengan penerapan machine olxtoto learning yang mampu menciptakan pola putaran lebih variatif. Sistem ini tidak lagi bergantung pada mekanisme tradisional, melainkan menggunakan data untuk menghasilkan pengalaman bermain yang terasa lebih hidup. Slot gacor terpercaya menghadirkan sensasi berbeda melalui algoritma yang terus belajar dari interaksi pemain. |
| 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 | null |
| api_docs_auth_walled | null |
| 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 picksR2DTools
0
/ 100 (rubric v1.1)Website Monitoring
Not advertised
0
No
Sales-led
0 / 0
Auth-walled
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
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