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How Requesty’s scores are calculated

The full audit trail, recomputed from the verdict data at build time through the same code that produced the leaderboard: verdict × quality × story weight per cell, cells sum to dimension scores, dimensions blend into the PA Score. Every number on the product page is reproducible from this page alone; for why the formula looks like this, see the methodology.

verdict factors: full ×1.0 · partial ×0.6 · disputed ×0.3 · none ×0.0 · n/a excluded from both sides · cell points = weight × quality × factor · cell max = weight × 10

PA Score18/100

Agent-ready 45.3 × 0.30 = 13.59

API quality 0.0 × 0.20 = 0.00

Openness 4.8 × 0.20 = 0.96

Built-in AI 0.0 × 0.15 = 0.00

Automation 21.6 × 0.15 = 3.24

(13.59 + 0.00 + 0.96 + 0.00 + 3.24) ÷ (0.30 + 0.20 + 0.20 + 0.15 + 0.15) = 17.79 ÷ 1.00 = 17.8

Scores are stored to 1 decimal; the product page’s pills round to whole numbers for display. Each dimension below shows the stories, verdicts, and cited evidence behind its number.

Agent-ready45.3/100×0.30 of the PA blend

Outside-in: can YOUR agent reach and drive this product — API, MCP, CLI, headless runs, agent docs.

Point an agent at llms.txt or agent-oriented docsweight 2

2 (weight) × 8 (quality) × 1.0 (full) = 16.0 of 20 max

  • [probe] https://docs.requesty.ai/llms.txt“PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for 300+ AI models (Claude, GPT, Gemini, DeepS”
  • [probe] https://docs.requesty.ai/quickstart.md“PROBE docs-md: HTTP 200 at https://docs.requesty.ai/quickstart.md > ## Documentation Index > Fetch the complete documentation index at: https://docs.requesty.ai/llms.txt > Use this file”

Run the product headlessly / in CI for automationweight 2

2 (weight) × 6 (quality) × 0.6 (partial) = 7.2 of 20 max

  • [claimed-docs] https://docs.requesty.ai/quickstart“If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
  • [claimed-docs] https://docs.requesty.ai/quickstart“base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
  • [claimed-docs] https://docs.requesty.ai/features/bring-your-own-keys.md“Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”

Plug MCP servers into this product so it can use their toolsweight 3

3 (weight) × 7 (quality) × 1.0 (full) = 21.0 of 30 max

  • [claimed-docs] https://docs.requesty.ai/features/mcp-gateway.md“The MCP (Model Context Protocol) Gateway enables AI coding assistants like Claude Code, Cursor, and Roo Code to securely connect to MCP servers through Requesty's unified API”

Connect an agent via an official MCP serverweight 3

3 (weight) × 7 (quality) × 1.0 (full) = 21.0 of 30 max

  • [claimed-docs] https://docs.requesty.ai/features/mcp-gateway.md“The MCP (Model Context Protocol) Gateway enables AI coding assistants like Claude Code, Cursor, and Roo Code to securely connect to MCP servers through Requesty's unified API”
  • [claimed-docs] https://docs.requesty.ai/integrations/claude-code.md“Using the Requesty integration, you can: Use 300+ models while coding, giving you flexibility to choose the best model for each task.”

Use an official CLIweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Drive the product through a documented public APIweight 3

3 (weight) × 8 (quality) × 1.0 (full) = 24.0 of 30 max

  • [claimed-docs] https://docs.requesty.ai/quickstart“If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
  • [claimed-docs] https://docs.requesty.ai/quickstart“base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
  • [claimed-docs] https://docs.requesty.ai/features/fallback-policies.md“Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when individual providers have issues.”
  • [claimed-docs] https://docs.requesty.ai/features/load-balancing-policies.md“Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollouts, and resource optimization.”
  • [claimed-docs] https://docs.requesty.ai/features/structured-outputs.md“Requesty makes every supported model speak structured JSON — from simple json_object mode to strict, schema-enforced json_schema mode.”
  • [probe] https://docs.requesty.ai/llms.txt“PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for 300+ AI models (Claude, GPT, Gemini, DeepS”
  • [probe] https://docs.requesty.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.ai/api/openapi.json, https://docs.requesty.ai/.well-known/openapi.json)”

Issue scoped/least-privilege API credentials for an agentweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

  • [claimed-docs] https://docs.requesty.ai/features/bring-your-own-keys.md“Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
  • [claimed-docs] https://www.requesty.ai“Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

Build against official SDKsweight 2

2 (weight) × 5 (quality) × 0.6 (partial) = 6.0 of 20 max

  • [claimed-docs] https://docs.requesty.ai/quickstart“If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
  • [claimed-docs] https://docs.requesty.ai/quickstart“base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
  • [probe] https://docs.requesty.ai/llms.txt“PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for 300+ AI models (Claude, GPT, Gemini, DeepS”

Subscribe to events via webhooksweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Agent-ready = 95.2 ÷ 210 × 100 = 45.3

API quality0.0/100×0.20 of the PA blend

The programmable surface once an agent is there — machine-readable spec, interactive docs, sandbox, versioning discipline.

Explore an interactive API reference with runnable examplesweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

  • [probe] https://docs.requesty.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.ai/api/openapi.json, https://docs.requesty.ai/.well-known/openapi.json)”
  • [claimed-docs] https://docs.requesty.ai/quickstart“If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
  • [claimed-docs] https://docs.requesty.ai/quickstart“base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”

Download a machine-readable API spec (OpenAPI or equivalent)weight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

  • [probe] https://docs.requesty.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.ai/api/openapi.json, https://docs.requesty.ai/.well-known/openapi.json)”

Test against a sandbox environment without touching production dataweight 1

n/a — not applicable to this product: excluded from numerator and denominator

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Rely on versioned APIs with a documented deprecation policyweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

  • [probe] https://docs.requesty.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.ai/api/openapi.json, https://docs.requesty.ai/.well-known/openapi.json)”

API quality = 0.0 ÷ 60 × 100 = 0.0

Openness4.8/100×0.20 of the PA blend

Can you leave, inspect, or self-host — data export, open source, portability.

Do everything through the API that I can do in the UIweight 2

2 (weight) × 4 (quality) × 0.6 (partial) = 4.8 of 20 max

  • [claimed-docs] https://docs.requesty.ai/features/fallback-policies.md“Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when individual providers have issues.”
  • [claimed-docs] https://docs.requesty.ai/features/load-balancing-policies.md“Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollouts, and resource optimization.”
  • [claimed-docs] https://docs.requesty.ai/features/bring-your-own-keys.md“Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
  • [claimed-docs] https://docs.requesty.ai/features/guardrails.md“Guardrails scan AI request content for sensitive information before it reaches a model provider.”
  • [claimed-docs] https://docs.requesty.ai/features/usage-analytics.md“Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, tokens, cache savings, and latency, all in real-time.”
  • [probe] https://docs.requesty.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.ai/api/openapi.json, https://docs.requesty.ai/.well-known/openapi.json)”

Export all of my data in open formats and leaveweight 3

3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max

  • [claimed-docs] https://docs.requesty.ai/features/usage-analytics.md“Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, tokens, cache savings, and latency, all in real-time.”

Read the product's source under an open licenseweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Self-host the core productweight 3

3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Openness = 4.8 ÷ 100 × 100 = 4.8

Built-in AI0.0/100×0.15 of the PA blend

Inside-out: how agentic the product itself is for its users — built-in assistants, autonomous features.

Get AI-generated insights and suggestions from my data inside the productweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

  • [claimed-docs] https://docs.requesty.ai/features/usage-analytics.md“Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, tokens, cache savings, and latency, all in real-time.”

Set up automations that run autonomously in the backgroundweight 2

n/a — not applicable to this product: excluded from numerator and denominator

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Delegate tasks to a built-in AI assistant inside the productweight 3

n/a — not applicable to this product: excluded from numerator and denominator

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Operate the product with natural-language commandsweight 2

n/a — not applicable to this product: excluded from numerator and denominator

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Built-in AI = 0.0 ÷ 20 × 100 = 0.0

Automation21.6/100×0.15 of the PA blend

Depth of automation primitives — rules, scheduling, bulk operations, webhooks.

Perform bulk operations across many items at onceweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Define rules that trigger actions automatically on eventsweight 3

3 (weight) × 6 (quality) × 0.6 (partial) = 10.8 of 30 max

  • [claimed-docs] https://docs.requesty.ai/features/fallback-policies.md“Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when individual providers have issues.”
  • [claimed-docs] https://docs.requesty.ai/features/fallback-policies.md“Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in the chain.”
  • [claimed-docs] https://docs.requesty.ai/features/load-balancing-policies.md“Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollouts, and resource optimization.”
  • [claimed-docs] https://docs.requesty.ai/features/guardrails.md“Guardrails scan AI request content for sensitive information before it reaches a model provider.”

Schedule recurring jobs or workflowsweight 2

n/a — not applicable to this product: excluded from numerator and denominator

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Version, review, and roll back my automationsweight 1

n/a — not applicable to this product: excluded from numerator and denominator

no evidence cited — the verdict rests on absence of evidence, re-checked on refresh

Automation = 10.8 ÷ 50 × 100 = 21.6