Rank #2 of 7 in Model Gateways & Routers
Showcase


Verified integrations
Connections to other tracked products — hover a chip for the verbatim evidence quote behind it.
By theme — the product's score on each story themeBy theme
Agenticness — how well agents can access and operate the productAgenticnessevidence →
How well agents can access and operate the product
Automation depth — how much of the product can run unattendedAutomation depthevidence →
How much of the product can run unattended
Caching performance — stories about caching performance in this arenaCaching performanceevidence →
Stories about caching performance in this arena
Cost controls — stories about cost controls in this arenaCost controlsevidence →
Stories about cost controls in this arena
Key management — stories about key management in this arenaKey managementevidence →
Stories about key management in this arena
Observability — seeing what the system is doing — logs, metrics, traces, alertsObservabilityevidence →
Seeing what the system is doing — logs, metrics, traces, alerts
Openness — open source, data portability, and self-hosting storiesOpennessevidence →
Open source, data portability, and self-hosting stories
Privacy posture — data-handling and privacy storiesPrivacy postureevidence →
Data-handling and privacy stories
Routing resilience — stories about routing resilience in this arenaRouting resilienceevidence →
Stories about routing resilience in this arena
Streaming tools — stories about streaming tools in this arenaStreaming toolsevidence →
Stories about streaming tools in this arena
Unified api — stories about unified api in this arenaUnified apievidence →
Stories about unified api in this arena
Story verdicts — every judged story with its evidenceStory verdicts
What’s free: 4 free · 1 paid · 1 enterprise · 26 not stated in evidence
Follow the green: where the map greys out is where OpenRouter stops today. ✓ full · ~ partial · ! disputed · — none · n/a not applicable.
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
API surface
Drive the product through a documented public API
✓10/10
unlocks → Webhooks · Versioning policy · API sandbox · Official CLI · Full data export
Subscribe to events via webhooks
—–
Build against official SDKs
~5/10
Issue scoped/least-privilege API credentials for an agent
~7/10
Connect an agent via an official MCP server
✓8/10
Download a machine-readable API spec (OpenAPI or equivalent)
✓9/10
Rely on versioned APIs with a documented deprecation policy
—–
Test against a sandbox environment without touching production data
—–
Explore an interactive API reference with runnable examples
✓8/10
Docs for agents
Point an agent at llms.txt or agent-oriented docs
✓9/10
Agentic features
Delegate tasks to a built-in AI assistant inside the product
n/an/a
Operate the product with natural-language commands
~4/10
Plug MCP servers into this product so it can use their tools
—0/10
Get AI-generated insights and suggestions from my data inside the product
n/an/a
Set up automations that run autonomously in the background
n/an/a
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
Caching performance — stories about caching performance in this arenaCaching performance
Stories about caching performance in this arena
Cost controls — stories about cost controls in this arenaCost controls
Stories about cost controls in this arena
Key management — stories about key management in this arenaKey management
Stories about key management in this arena
Observability — seeing what the system is doing — logs, metrics, traces, alertsObservability
Seeing what the system is doing — logs, metrics, traces, alerts
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
Routing resilience — stories about routing resilience in this arenaRouting resilience
Stories about routing resilience in this arena
Configure automatic fallback to another model or provider when one fails
✓9/10
Load-balance traffic across providers, deployments, or keys by weight, latency, or cost
✓7/10
My agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rules
✓8/10
Smooth provider rate limits by spreading traffic across keys and queuing or throttling requests
~5/10
Set automatic retry policies for transient provider errors
~7/10
Streaming tools — stories about streaming tools in this arenaStreaming tools
Stories about streaming tools in this arena
Unified api — stories about unified api in this arenaUnified api
Stories about unified api in this arena
Sorted by importance (agentic first) (high → low) · 50/50 stories · click a row’s chevron for the rationale and evidence
Drive the product through a documented public API G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 10/10 | Tprobed | |
Connect an agent via an official MCP server G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 8/10 | Tprobed | |
Plug MCP servers into this product so it can use their tools G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | none | 0/10 | ||
Delegate tasks to a built-in AI assistant inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | n/a | untested | none yet | |
Download a machine-readable API spec (OpenAPI or equivalent) G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | fullfree | 9/10 | Tprobed | |
Point an agent at llms.txt or agent-oriented docs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | fullfree | 9/10 | Tprobed | |
Explore an interactive API reference with runnable examples G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | fullfree | 8/10 | Tprobed | |
Issue scoped/least-privilege API credentials for an agent G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 7/10 | Xcommunity | |
Run the product headlessly / in CI for automation G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 7/10 | Tprobed | |
Build against official SDKs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 5/10 | Tprobed | |
Operate the product with natural-language commands G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 4/10 | Tprobed | |
Get AI-generated insights and suggestions from my data inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | n/a | untested | none yet | |
Rely on versioned APIs with a documented deprecation policy G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Set up automations that run autonomously in the background G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | n/a | untested | none yet | |
Subscribe to events via webhooks G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Use an official CLI G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Test against a sandbox environment without touching production data G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 1 | none | untested | none yet | |
Call many model providers through one consistent API C One endpoint | developer | Unified api — stories about unified api in this arenaUnified api | 3 | fullpaid | 9/10 | Tprobed | |
Configure automatic fallback to another model or provider when one fails C Fallbacks | platform engineer | Routing resilience — stories about routing resilience in this arenaRouting resilience | 3 | full | 9/10 | Xcommunity | |
Point existing OpenAI-compatible code at the gateway by changing only the base URL and key C Compatibility | developer | Unified api — stories about unified api in this arenaUnified api | 3 | full | 9/10 | Tprobed | |
Make tool and function calls across different providers with a consistent schema C Tool calling | developer | Streaming tools — stories about streaming tools in this arenaStreaming tools | 3 | full | 8/10 | Xcommunity | |
Mint gateway-managed keys for teams and apps without exposing raw provider keys C Virtual keys | platform engineer | Key management — stories about key management in this arenaKey management | 3 | full | 8/10 | Xcommunity | |
My agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rules C Policy routing | ai-native user | Routing resilience — stories about routing resilience in this arenaRouting resilience | 3 | full | 8/10 | Xcommunity | |
Stream token-by-token responses through the gateway from any provider C Streaming | developer | Streaming tools — stories about streaming tools in this arenaStreaming tools | 3 | full | 8/10 | Xcommunity | |
Prevent my data from being used to train AI models G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 3 | partial | 6/10 | Xcommunity | |
Provision gateways, keys, and budgets programmatically through an admin API C Programmatic admin | ai-native user | Key management — stories about key management in this arenaKey management | 3 | partial | 6/10 | Xcommunity | |
Set hard budgets and spend limits per key, team, or user C Budgets | platform engineer | Cost controls — stories about cost controls in this arenaCost controls | 3 | partial | 6/10 | Xcommunity | |
Track spend per model, key, team, or user across all providers in one place C Spend tracking | platform engineer | Cost controls — stories about cost controls in this arenaCost controls | 3 | partial | 6/10 | Xcommunity | |
Define rules that trigger actions automatically on events G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 3 | none | untested | none yet | |
Export all of my data in open formats and leave G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | none | untested | none yet | |
Inspect logged requests and responses with latency, token counts, and cost attached C Logs | platform engineer | Observability — seeing what the system is doing — logs, metrics, traces, alertsObservability | 3 | none | untested | none yet | |
Self-host the core product G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | n/a | untested | none yet | |
Bring my own provider API keys and have the gateway use them for my traffic G Byok | developer | Key management — stories about key management in this arenaKey management | 2 | full | 9/10 | Xcommunity | |
Browse or query a catalog of available models with pricing and context-window metadata G Catalog | developer | Unified api — stories about unified api in this arenaUnified api | 2 | fullfree | 9/10 | Tprobed | |
Give an autonomous agent its own key with budget and rate guardrails so it cannot run away on spend C Agent guardrails | ai-native user | Cost controls — stories about cost controls in this arenaCost controls | 2 | full | 8/10 | Xcommunity | |
Cache responses at the gateway to cut cost and latency on repeated requests C Caching | developer | Caching performance — stories about caching performance in this arenaCaching performance | 2 | full | 7/10 | Cclaimed | |
Load-balance traffic across providers, deployments, or keys by weight, latency, or cost C Load balancing | platform engineer | Routing resilience — stories about routing resilience in this arenaRouting resilience | 2 | full | 7/10 | Xcommunity | |
Set automatic retry policies for transient provider errors C Retries | platform engineer | Routing resilience — stories about routing resilience in this arenaRouting resilience | 2 | partial | 7/10 | Xcommunity | |
Choose where my data is stored (region/residency) G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | partialenterprise | 6/10 | Xcommunity | |
Do everything through the API that I can do in the UI G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | partial | 6/10 | Tprobed | |
Control data retention and deletion G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | partial | 5/10 | Xcommunity | |
Run traffic through gateway infrastructure that adds minimal latency overhead to provider calls C Latency | platform engineer | Caching performance — stories about caching performance in this arenaCaching performance | 2 | partial | 5/10 | Xcommunity | |
Smooth provider rate limits by spreading traffic across keys and queuing or throttling requests C Rate limits | platform engineer | Routing resilience — stories about routing resilience in this arenaRouting resilience | 2 | partial | 5/10 | Xcommunity | |
Opt out of telemetry and usage tracking G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | partial | 4/10 | Xcommunity | |
Perform bulk operations across many items at once G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | none | untested | none yet | |
Read the product's source under an open license G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | none | untested | none yet | |
Schedule recurring jobs or workflows G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | n/a | untested | none yet | |
Export gateway logs and traces to my own observability stack G Integrations | developer | Observability — seeing what the system is doing — logs, metrics, traces, alertsObservability | 1 | none | untested | none yet | |
Request structured JSON-schema outputs across providers C Tool calling | developer | Streaming tools — stories about streaming tools in this arenaStreaming tools | 1 | none | untested | none yet | |
Version, review, and roll back my automations G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 1 | n/a | untested | none yet |
Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 26 stories with headroom
What would move OpenRouter’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.
Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools
nonemoves agent-readyimpact 45
Evidence only shows OpenRouter publishing its own MCP server so external AI tools/editors can pull OpenRouter data (docs-14, docs-26, docs-34, probe-3) — this is OpenRouter acting as an MCP server for other clients, not OpenRouter itself consuming/plugging in external MCP servers to gain their tools.
Automation depth — how much of the product can run unattendedDefine rules that trigger actions automatically on events
nonemoves PA Scoreimpact 30
OpenRouter is an LLM routing/API gateway; nothing in the evidence describes user-defined event-driven rules or triggers (e.g., webhooks, if-this-then-that automations) that fire actions automatically.
Openness — open source, data portability, and self-hosting storiesExport all of my data in open formats and leave
nonemoves PA Scoreimpact 30
The evidence pack covers API routing, model access, MCP server, and billing features, but contains no mention of any user data export capability (usage logs, account data, chat history) in open formats or account portability/closure process — the axis is applicable to a SaaS platform storing usage/billing data, but no supporting evidence exists.
Observability — seeing what the system is doing — logs, metrics, traces, alertsInspect logged requests and responses with latency, token counts, and cost attached
nonemoves PA Scoreimpact 30
Missing: activity/logs dashboard documentation, per-request latency metrics, per-request token count and cost attribution evidence.
Agenticness — how well agents can access and operate the productUse an official CLI
nonemoves agent-readyimpact 30
OpenRouter is an API/model-routing platform for which an official CLI would be a plausible ecosystem tool, but the evidence pack contains no mention of any official OpenRouter CLI — only SDK compatibility, REST API, MCP server, and web UI are documented.
Agenticness — how well agents can access and operate the productSubscribe to events via webhooks
nonemoves agent-readyimpact 30
No evidence in the pack mentions webhooks or event subscription mechanisms of any kind for OpenRouter; the documented features (routing, caching, key management, MCP server) do not include webhook support.
Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy
nonemoves API qualityimpact 30
The evidence pack covers routing, fallbacks, caching, BYOK, key management, and privacy settings, but nowhere documents API versioning (e.g., v1/v2 endpoints) or a formal deprecation policy/timeline for endpoints or models.
Automation depth — how much of the product can run unattendedPerform bulk operations across many items at once
nonemoves PA Scoreimpact 20
Missing: batch API or bulk job submission endpoint, evidence of processing many items in a single call, bulk data/export operations.
Showing the top 8 of 26 — every none/partial verdict in the story verdicts table is headroom.
Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.
Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map6 surfaces · 32 covered stories
Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.
docs32 stories
- Point an agent at llms.txt or agent-oriented docs
- Run the product headlessly / in CI for automation
- Connect an agent via an official MCP server
- Drive the product through a documented public API
- Issue scoped/least-privilege API credentials for an agent
- Build against official SDKs
- Operate the product with natural-language commands
- Explore an interactive API reference with runnable examples
- Download a machine-readable API spec (OpenAPI or equivalent)
- Cache responses at the gateway to cut cost and latency on repeated requests
- Run traffic through gateway infrastructure that adds minimal latency overhead to provider calls
- Give an autonomous agent its own key with budget and rate guardrails so it cannot run away on spend
- Set hard budgets and spend limits per key, team, or user
- Track spend per model, key, team, or user across all providers in one place
- Bring my own provider API keys and have the gateway use them for my traffic
- Provision gateways, keys, and budgets programmatically through an admin API
- Mint gateway-managed keys for teams and apps without exposing raw provider keys
- Do everything through the API that I can do in the UI
- Choose where my data is stored (region/residency)
- Prevent my data from being used to train AI models
- Control data retention and deletion
- Opt out of telemetry and usage tracking
- Configure automatic fallback to another model or provider when one fails
- Load-balance traffic across providers, deployments, or keys by weight, latency, or cost
- My agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rules
- Smooth provider rate limits by spreading traffic across keys and queuing or throttling requests
- Set automatic retry policies for transient provider errors
- Stream token-by-token responses through the gateway from any provider
- Make tool and function calls across different providers with a consistent schema
- Browse or query a catalog of available models with pricing and context-window metadata
- Point existing OpenAI-compatible code at the gateway by changing only the base URL and key
- Call many model providers through one consistent API
Hacker News24 stories
- Drive the product through a documented public API
- Issue scoped/least-privilege API credentials for an agent
- Run traffic through gateway infrastructure that adds minimal latency overhead to provider calls
- Give an autonomous agent its own key with budget and rate guardrails so it cannot run away on spend
- Set hard budgets and spend limits per key, team, or user
- Track spend per model, key, team, or user across all providers in one place
- Bring my own provider API keys and have the gateway use them for my traffic
- Provision gateways, keys, and budgets programmatically through an admin API
- Mint gateway-managed keys for teams and apps without exposing raw provider keys
- Do everything through the API that I can do in the UI
- Choose where my data is stored (region/residency)
- Prevent my data from being used to train AI models
- Control data retention and deletion
- Opt out of telemetry and usage tracking
- Configure automatic fallback to another model or provider when one fails
- Load-balance traffic across providers, deployments, or keys by weight, latency, or cost
- My agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rules
- Smooth provider rate limits by spreading traffic across keys and queuing or throttling requests
- Set automatic retry policies for transient provider errors
- Stream token-by-token responses through the gateway from any provider
- Make tool and function calls across different providers with a consistent schema
- Browse or query a catalog of available models with pricing and context-window metadata
- Point existing OpenAI-compatible code at the gateway by changing only the base URL and key
- Call many model providers through one consistent API
OpenAPI spec7 stories
- Point an agent at llms.txt or agent-oriented docs
- Run the product headlessly / in CI for automation
- Drive the product through a documented public API
- Build against official SDKs
- Explore an interactive API reference with runnable examples
- Download a machine-readable API spec (OpenAPI or equivalent)
- Do everything through the API that I can do in the UI
API reference5 stories
llms.txt5 stories
- Point an agent at llms.txt or agent-oriented docs
- Drive the product through a documented public API
- Download a machine-readable API spec (OpenAPI or equivalent)
- Point existing OpenAI-compatible code at the gateway by changing only the base URL and key
- Call many model providers through one consistent API
openrouter.ai4 stories
- Configure automatic fallback to another model or provider when one fails
- My agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rules
- Set automatic retry policies for transient provider errors
- Browse or query a catalog of available models with pricing and context-window metadata
Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence
14 of 15 testable claims verified · 0 contradicted → integrity 93/100
19 distinct capability claims found in OpenRouter’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.
14
Verified
1
Unverified
0
Contradicted
17
Undersold
Verified (15)
“Access hundreds of AI models through one unified API endpoint”
Call many model providers through one consistent APIfullproof ↗
“Specify an ordered list of models so requests automatically fall back to the next one on error or refusal”
Configure automatic fallback to another model or provider when one failsfullproof ↗
“Requests are routed and load-balanced across top providers to maximize uptime”
Load-balance traffic across providers, deployments, or keys by weight, latency, or costfullproof ↗
“Tool calling interface is standardized across models and providers”
Make tool and function calls across different providers with a consistent schemafullproof ↗
“API endpoints let you programmatically create, manage, and rotate API keys”
Provision gateways, keys, and budgets programmatically through an admin APIpartialproof ↗
“Supports bringing your own provider API keys (BYOK) for direct rate-limit and cost control”
Bring my own provider API keys and have the gateway use them for my trafficfullproof ↗
“Workspace budgets let you cap spend over daily, weekly, monthly, or lifetime intervals, auto-blocking once reached”
Set hard budgets and spend limits per key, team, or userpartialproof ↗
“Supports streaming token-by-token responses from any model”
Stream token-by-token responses through the gateway from any providerfullproof ↗
“Enterprise customers can enable in-region (EU/US) processing so data doesn't leave the selected region”
Choose where my data is stored (region/residency)partialproof ↗
“An official MCP server exposes live OpenRouter data (models, prices, credits, rankings, docs) and test messaging inside AI tools/editors”
“OpenAI SDK can be pointed at OpenRouter as a drop-in replacement”
Point existing OpenAI-compatible code at the gateway by changing only the base URL and keyfullproof ↗
“Requests can be customized for routing behavior via a provider object in the request body”
Load-balance traffic across providers, deployments, or keys by weight, latency, or costfullproof ↗
“Account settings let you opt in/out of routing to providers that may train on your data”
Prevent my data from being used to train AI modelspartialproof ↗
“An interactive Request Builder generates API requests in your language of choice”
Explore an interactive API reference with runnable examplesfullproof ↗
“Full model catalog can be browsed on the site or listed programmatically via a models API endpoint”
Browse or query a catalog of available models with pricing and context-window metadatafullproof ↗
Unverified (2)
“Cached responses are returned instantly with zero billing, cutting latency and cost”
Cache responses at the gateway to cut cost and latency on repeated requestsfullproof ↗
“Sticky routing sends follow-up requests to the same provider endpoint to maximize cache hits”
Cache responses at the gateway to cut cost and latency on repeated requestsfullproof ↗
Undersold (17)
Point an agent at llms.txt or agent-oriented docsfullproof ↗
Run the product headlessly / in CI for automationfullproof ↗
Drive the product through a documented public APIfullproof ↗
Issue scoped/least-privilege API credentials for an agentpartialproof ↗
Operate the product with natural-language commandspartialproof ↗
Download a machine-readable API spec (OpenAPI or equivalent)fullproof ↗
Run traffic through gateway infrastructure that adds minimal latency overhead to provider callspartialproof ↗
Give an autonomous agent its own key with budget and rate guardrails so it cannot run away on spendfullproof ↗
Track spend per model, key, team, or user across all providers in one placepartialproof ↗
Mint gateway-managed keys for teams and apps without exposing raw provider keysfullproof ↗
Do everything through the API that I can do in the UIpartialproof ↗
My agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rulesfullproof ↗
Smooth provider rate limits by spreading traffic across keys and queuing or throttling requestspartialproof ↗
Set automatic retry policies for transient provider errorspartialproof ↗
Claims outside our story set (2)
Real capability claims found in OpenRouter’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.
“A 'latest' model alias automatically resolves to the newest flagship model without code changes”
source ↗“Individual requests or account-wide settings can restrict which providers' data policies are allowed”
source ↗
Pricing signals
- 5.5%gateway feepay-as-you-goPay-as-you-go platform fee applied on top of model inference pricingsource ↗as of 2026-09-07
- 0%gateway feefree tierFree tier: 25+ free models, 4 free providers, limited to 50 requests/day, free models onlysource ↗as of 2026-09-07
- 5%gateway feepay-as-you-goEnterprise: no platform fee up to $200,000/month of list price inference, 5% fee thereaftersource ↗as of 2026-09-07
Extracted verbatim from the vendor’s own pricing page — hover a figure for the exact quote.
Business model
Pay-as-you-go: buy credits and pay provider list price per token plus a small platform fee on credit purchases; enterprise plans are custom.
pricing ↗Score trend
How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.
Flag
⚑ Flag a verdictThink a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.
For agents
Agent surface uptime llms.txt 100% · openapi.json 100% (30d, checked every 6h since Sep 8 '26)
