{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-judge0--judge0","slug":"judge0--judge0","name":"judge0","type":"mcp","url":"https://judge0.com","page_url":"https://unfragile.ai/judge0--judge0","categories":["mcp-servers"],"tags":["ai-agent-tools","ai-agents","ai-tools","code-execution","code-executor","code-runner","competitive-programming","online-compiler","online-judge","online-judges","onlinejudge","onlinejudge-solution"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-judge0--judge0__cap_0","uri":"capability://automation.workflow.sandboxed.code.execution.with.resource.limits","name":"sandboxed-code-execution-with-resource-limits","description":"Executes untrusted code in isolated sandbox environments using the Isolate sandbox system with configurable resource constraints (CPU time, memory, disk I/O, wall clock time). Each submission runs in a separate process-isolated container, preventing code from accessing host system resources or other submissions. The system applies per-language compiler options and runtime arguments while capturing detailed execution telemetry including stdout, stderr, compilation output, exit codes, and resource consumption metrics.","intents":["I need to safely run student code submissions without risk of system compromise","I want to enforce execution time limits to prevent infinite loops from blocking my platform","I need detailed execution metrics (runtime, memory usage) to provide feedback to users","I want to support multiple programming languages with language-specific compiler configurations"],"best_for":["competitive programming platforms building online judges","e-learning platforms executing student code safely","recruitment/assessment systems running candidate code","AI agents that need to validate generated code before deployment"],"limitations":["Isolate sandbox is Linux-only; no native Windows/macOS support without virtualization","Resource limit enforcement has ~5-10% variance depending on system load and kernel scheduling","Network access is blocked by default; no outbound HTTP/socket connections from sandboxed code","Execution time limits are wall-clock based, not CPU-time based, affecting multi-threaded code accuracy","File system isolation prevents reading files outside the submission directory"],"requires":["Linux kernel 4.4+ with cgroup support for resource limiting","Isolate sandbox system installed and configured on execution worker","PostgreSQL 9.6+ for storing submission metadata and results","Redis 4.0+ for job queue and result caching","60+ language compilers/interpreters installed on worker nodes (gcc, python3, node, etc.)"],"input_types":["source code (single or multi-file)","compiler flags and command-line arguments","stdin input for program execution","resource limit specifications (CPU time, memory)"],"output_types":["stdout and stderr streams","compilation output and error messages","exit code and signal information","execution metrics (runtime in ms, memory in KB, wall clock time)"],"categories":["automation-workflow","code-execution","sandboxing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_1","uri":"capability://code.generation.editing.multi.language.compilation.and.execution","name":"multi-language-compilation-and-execution","description":"Supports 60+ programming languages by maintaining a registry of language-specific compilers, interpreters, and runtime configurations. The system maps language identifiers to appropriate build and execution commands, applies language-specific compiler flags (e.g., -O2 for C++, --release for Rust), and handles both compiled and interpreted languages transparently. Language support is extensible through configuration without code changes, allowing operators to add new languages by defining compiler paths and execution templates.","intents":["I want to support C++, Python, Java, JavaScript, and 50+ other languages in my platform","I need to apply language-specific optimizations (e.g., -O2 for C++, -Wall for warnings)","I want to add a new language without modifying the core system code","I need consistent execution behavior across different language ecosystems"],"best_for":["polyglot competitive programming platforms","educational platforms teaching multiple languages","recruitment platforms assessing candidates across tech stacks","AI code generation systems validating output in diverse languages"],"limitations":["Adding a new language requires installing its compiler/interpreter on all worker nodes","Language versions are fixed per deployment; no per-submission version selection","Some languages have significantly slower startup times (Java ~1-2s vs C++ ~50ms)","Interpreted languages have no compile-time error detection; errors only surface at runtime","No built-in support for language-specific package managers (pip, npm, cargo) for external dependencies"],"requires":["Language compiler/interpreter binaries installed on worker nodes","Language configuration in Judge0 database (compiler path, execution command template)","Sufficient disk space for compiled artifacts (~100MB per language minimum)","Language-specific runtime libraries (libc, libstdc++, etc.) available on worker"],"input_types":["source code in any supported language","language identifier (numeric ID or name)","custom compiler flags and arguments","stdin input for program execution"],"output_types":["compiled binary (for compiled languages)","execution output (stdout/stderr)","compilation errors and warnings","language-specific runtime errors"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_10","uri":"capability://automation.workflow.health.monitoring.and.system.diagnostics","name":"health-monitoring-and-system-diagnostics","description":"Provides health check endpoints that report API server status, worker availability, Redis connectivity, database connectivity, and queue depth. The system exposes metrics including submission throughput, average execution time, worker utilization, and queue latency. Health checks can be used by load balancers to route traffic away from unhealthy instances. Diagnostic endpoints provide detailed information about system state for debugging and capacity planning.","intents":["I want to monitor Judge0 health in my infrastructure","I need to detect when workers are down or overloaded","I want to track submission throughput and execution latency","I need to diagnose queue backlog and performance issues"],"best_for":["production deployments requiring monitoring and alerting","platforms with SLA requirements","infrastructure teams managing Judge0 deployments","capacity planning and performance optimization"],"limitations":["Health checks are point-in-time snapshots; transient failures may not be detected","Metrics are not persisted; historical data requires external monitoring system","No built-in alerting; requires integration with monitoring tools (Prometheus, Datadog)","Queue depth metric may be inaccurate during high load","Worker availability is based on heartbeat; dead workers may take time to be detected"],"requires":["Monitoring system (Prometheus, Datadog, New Relic) for metrics collection","Load balancer capable of consuming health check endpoints","Network access to health check endpoints"],"input_types":["optional: detailed=true parameter for verbose diagnostics"],"output_types":["JSON object with status, worker count, queue depth, metrics","HTTP 200 OK if healthy, HTTP 503 Service Unavailable if unhealthy"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_11","uri":"capability://safety.moderation.configurable.resource.limits.and.enforcement","name":"configurable-resource-limits-and-enforcement","description":"Allows operators to configure per-language and global resource limits including CPU time (seconds), wall clock time (seconds), memory (megabytes), disk space (megabytes), and process count. Limits are enforced by the Isolate sandbox using cgroups and system calls. The system supports different limit profiles for different languages (e.g., Java gets higher memory limit than C++). Clients can optionally override limits within operator-defined bounds. Limit violations trigger appropriate status codes (Time Limit Exceeded, Memory Limit Exceeded).","intents":["I want to prevent infinite loops from blocking execution workers","I need to limit memory usage to prevent out-of-memory crashes","I want to allow different languages to have different resource limits","I need to prevent disk exhaustion from large file writes"],"best_for":["platforms executing untrusted code","systems with limited hardware resources","competitive programming platforms with standardized limits","educational platforms teaching resource-aware programming"],"limitations":["CPU time limits are wall-clock based, not CPU-time based; multi-threaded code may exceed limits","Memory limits are approximate; actual OOM may occur slightly above configured limit","Disk space limits are per-submission; no global disk quota across submissions","Process count limits may be too restrictive for languages that spawn subprocesses","Limit enforcement has ~5-10% variance depending on system load and kernel scheduling"],"requires":["Linux cgroup support for resource limiting","Isolate sandbox configured with resource limit enforcement","Operator configuration of per-language limits"],"input_types":["cpu_time_limit (seconds)","memory_limit (megabytes)","disk_limit (megabytes)","wall_time_limit (seconds)"],"output_types":["status code indicating limit violation (TLE, MLE, etc.)","actual resource usage (time, memory) for comparison with limits"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_12","uri":"capability://memory.knowledge.result.caching.and.ttl.management","name":"result-caching-and-ttl-management","description":"Caches execution results in Redis with configurable time-to-live (TTL), typically 24 hours. Clients can retrieve cached results without re-executing code if the same submission is requested multiple times. The cache key is derived from source code hash, language, and compiler flags, enabling deduplication of identical submissions. Expired results are automatically purged from Redis. Clients can optionally bypass cache and force re-execution.","intents":["I want to avoid re-executing identical code submissions","I need to reduce execution latency for repeated submissions","I want to save execution resources by caching results","I need to manage result storage with automatic expiration"],"best_for":["platforms with repeated submissions (e.g., students resubmitting same code)","systems with limited execution capacity","platforms prioritizing latency over freshness","competitive programming platforms with code reuse"],"limitations":["Cache hits only occur for identical code, language, and compiler flags","Results expire after TTL; long-term storage requires external archival","Cache key collisions are theoretically possible (hash-based); no collision detection","Redis memory is limited; large result sets may evict older entries","No cache invalidation mechanism; stale results may be served if code semantics change","Cache is not distributed; each Redis instance has independent cache"],"requires":["Redis instance for caching","Sufficient Redis memory for result storage","Client-side cache bypass logic if needed"],"input_types":["source code (for cache key derivation)","language identifier","compiler flags","optional: skip_cache=true to bypass cache"],"output_types":["cached execution results if cache hit","fresh execution results if cache miss or bypass"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_13","uri":"capability://automation.workflow.containerized.deployment.and.docker.support","name":"containerized-deployment-and-docker-support","description":"Provides Docker container images for easy deployment of Judge0 API server and worker processes. The Dockerfile includes all dependencies (Ruby, PostgreSQL client, Redis client, language compilers) and is optimized for production use. Deployment is simplified to docker-compose or Kubernetes manifests. The system supports environment variable configuration for database, Redis, and resource limits, enabling deployment without code changes. Docker images are published to Docker Hub for easy access.","intents":["I want to deploy Judge0 quickly without manual dependency installation","I need to run Judge0 in Kubernetes or Docker Swarm","I want to scale workers horizontally using container orchestration","I need reproducible deployments across development and production"],"best_for":["cloud-native deployments (AWS, GCP, Azure)","Kubernetes-based infrastructure","teams using Docker for all services","rapid prototyping and MVP development"],"limitations":["Docker images are Linux-only; no native Windows/macOS support","Container startup time is ~2-5 seconds; slower than native binaries","Nested sandboxing (Docker + Isolate) adds complexity; requires privileged containers","Docker image size is large (~2GB) due to language compiler inclusion","Network isolation between containers may interfere with multi-file submissions","Persistent storage requires external volumes; no built-in state management"],"requires":["Docker 20.10+ or Docker Desktop","Docker Compose 1.29+ for local development","Kubernetes 1.20+ for production deployment","External PostgreSQL and Redis instances (or docker-compose services)","Sufficient disk space for Docker images (~2GB per image)"],"input_types":["environment variables for configuration (DB_HOST, REDIS_URL, etc.)","docker-compose.yml or Kubernetes manifests"],"output_types":["running Docker containers with Judge0 API and workers"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_2","uri":"capability://automation.workflow.synchronous.and.asynchronous.execution.modes","name":"synchronous-and-asynchronous-execution-modes","description":"Provides dual execution modes: synchronous mode (wait=true) where the client blocks until execution completes and receives results immediately, and asynchronous mode (wait=false) where the client receives a submission token and polls for results or receives webhook callbacks. The system uses Redis-backed job queues and background worker processes to decouple submission acceptance from execution, enabling horizontal scaling. Asynchronous mode supports webhook callbacks to notify clients when execution completes, eliminating polling overhead.","intents":["I want my API to return results immediately for quick code snippets without blocking","I need to handle high-volume submissions without blocking the API server","I want to notify my frontend when code execution completes via webhook instead of polling","I need to scale execution workers independently from the API server"],"best_for":["high-throughput competitive programming platforms with thousands of concurrent submissions","web-based IDEs that need responsive UI feedback","batch assessment systems processing hundreds of submissions","AI agents that need non-blocking code validation"],"limitations":["Synchronous mode has a timeout (typically 30-60s); longer-running code must use async mode","Asynchronous mode introduces latency (typically 100-500ms) due to job queue processing","Webhook callbacks require client to expose a publicly accessible endpoint; not suitable for client-side-only applications","No built-in result persistence; results expire after configurable TTL (typically 24 hours)","Job queue can become backlogged during traffic spikes, increasing wait time for async submissions"],"requires":["Redis instance for job queue and result caching","Background worker processes running (separate from API server)","For async mode: publicly accessible webhook endpoint on client side","API client capable of polling or receiving HTTP callbacks"],"input_types":["source code","language identifier","wait parameter (true/false)","webhook URL (for async mode)","callback headers (optional authentication)"],"output_types":["Synchronous: immediate execution results (stdout, stderr, metrics)","Asynchronous: submission token immediately, results via polling or webhook callback"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_3","uri":"capability://code.generation.editing.multi.file.program.submission.and.compilation","name":"multi-file-program-submission-and-compilation","description":"Accepts multi-file program submissions where clients can submit multiple source files that are compiled and executed together as a single unit. The system extracts files to an isolated submission directory, applies language-specific build commands (e.g., make, gradle, cargo), and executes the resulting binary. This enables support for projects with headers, modules, and dependencies while maintaining sandbox isolation. The API accepts files as base64-encoded strings or raw binary data in JSON/multipart payloads.","intents":["I want to submit C++ projects with header files and multiple source files","I need to support Java projects with multiple classes and packages","I want to test Rust projects with Cargo.toml and module structure","I need to validate student projects that use build systems like make or gradle"],"best_for":["competitive programming platforms supporting complex projects","educational platforms teaching modular programming","assessment systems evaluating real-world project structure","AI code generation systems producing multi-file outputs"],"limitations":["File count is limited (typically 100 files per submission) to prevent resource exhaustion","Total submission size is capped (typically 50MB) to prevent disk exhaustion","Build system output (object files, intermediate artifacts) counts against disk quota","No support for external package managers (npm install, pip install) without pre-staging dependencies","File paths are flattened to prevent directory traversal attacks; relative paths may not work as expected"],"requires":["API client capable of encoding files as base64 or multipart form data","Build system tools installed on worker (make, gradle, cargo, etc.) if using build files","Sufficient disk space per submission (~100MB per submission)","Language compiler/interpreter supporting multi-file compilation"],"input_types":["array of files with names and base64-encoded content","language identifier","custom build command (optional)","entry point or main file specification"],"output_types":["compiled binary or interpreted execution output","build system output (compilation errors, warnings)","execution results (stdout, stderr, exit code)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_4","uri":"capability://data.processing.analysis.detailed.execution.result.telemetry.and.metrics","name":"detailed-execution-result-telemetry-and-metrics","description":"Captures comprehensive execution telemetry including stdout/stderr streams, compilation output, exit codes, signal information, execution time (milliseconds), memory usage (kilobytes), CPU time, and wall clock time. Results are structured as JSON with language-specific status codes (e.g., 'Accepted', 'Wrong Answer', 'Time Limit Exceeded', 'Runtime Error'). The system stores results in PostgreSQL and caches them in Redis for fast retrieval. Clients can retrieve full results immediately or via polling with optional filtering.","intents":["I want to show users why their code failed (compilation error, runtime error, timeout)","I need to track execution metrics for performance analysis and platform optimization","I want to detect Time Limit Exceeded vs Runtime Error to provide targeted feedback","I need to export execution data for analytics and reporting"],"best_for":["competitive programming platforms providing detailed feedback","educational platforms helping students debug code","assessment systems generating detailed reports","performance monitoring and platform optimization"],"limitations":["Stdout/stderr output is truncated (typically 64KB) to prevent database bloat","Memory usage measurement has ~5-10% variance depending on kernel memory accounting","Execution time is wall-clock time, not CPU time; multi-threaded code may show inflated times","Results expire after configurable TTL (typically 24 hours); long-term storage requires external archival","No built-in result filtering or search; clients must retrieve full results and filter client-side"],"requires":["PostgreSQL database for storing results","Redis for caching recent results","API client capable of parsing JSON result structures","Sufficient database storage (~1KB per submission minimum)"],"input_types":["submission token or ID","optional result filtering parameters"],"output_types":["JSON object with status code, stdout, stderr, compilation output","execution metrics (time_ms, memory_kb, cpu_time_ms)","exit code and signal information","language-specific status interpretation"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_5","uri":"capability://automation.workflow.distributed.job.queue.and.worker.scaling","name":"distributed-job-queue-and-worker-scaling","description":"Implements a Redis-backed job queue that decouples submission acceptance from execution, enabling horizontal scaling of worker processes. The API server enqueues submissions as jobs; background worker processes dequeue and execute them in parallel. Workers are stateless and can be added/removed dynamically without affecting the API. The system supports configurable worker concurrency, job timeout, and retry logic. Multiple worker instances can run on different machines, processing jobs from a shared Redis queue.","intents":["I want to scale execution capacity by adding more worker machines without changing the API","I need to handle traffic spikes without blocking the API server","I want to distribute execution load across multiple CPU cores and machines","I need to retry failed submissions automatically without manual intervention"],"best_for":["high-traffic competitive programming platforms","cloud-native deployments with auto-scaling requirements","platforms with variable load patterns (peak hours vs off-peak)","distributed systems requiring independent scaling of API and execution tiers"],"limitations":["Redis becomes a single point of failure; requires Redis HA setup (Sentinel, Cluster) for production","Job queue can become backlogged during traffic spikes, increasing submission latency","Worker processes consume memory per concurrent job; scaling is limited by available RAM","No built-in job prioritization; all submissions are processed FIFO","Retry logic is basic; no exponential backoff or dead-letter queue for permanently failed jobs","Cross-machine worker coordination requires shared storage for multi-file submissions"],"requires":["Redis instance (3.0+) for job queue","Background job processing library (e.g., Sidekiq for Ruby)","Multiple worker processes or machines","Shared storage (NFS, S3) for multi-file submissions if workers are on different machines","Network connectivity between API server and workers"],"input_types":["submission job with code, language, and execution parameters","worker configuration (concurrency, timeout)"],"output_types":["job status (queued, processing, completed)","execution results when job completes"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_6","uri":"capability://code.generation.editing.custom.compiler.flags.and.runtime.arguments","name":"custom-compiler-flags-and-runtime-arguments","description":"Allows clients to specify custom compiler flags (e.g., -O2, -Wall, -std=c++17) and runtime arguments that are passed to the language's compiler or interpreter. The system validates flags against a whitelist to prevent injection attacks, then applies them during compilation and execution. This enables clients to control optimization levels, enable warnings, specify language standards, and pass command-line arguments to the executed program.","intents":["I want to compile C++ with -O2 optimization for performance testing","I need to enable all compiler warnings (-Wall) to catch potential issues","I want to specify C++ standard (-std=c++17) for the submission","I need to pass command-line arguments to the executed program"],"best_for":["competitive programming platforms allowing optimization control","educational platforms teaching compiler flags and optimization","assessment systems testing code with specific compiler settings","performance benchmarking platforms"],"limitations":["Flag whitelist must be maintained; unknown flags are rejected for security","Some flags may have unintended side effects (e.g., -O3 may cause timeout)","No validation of flag combinations; conflicting flags may produce unexpected behavior","Flags are applied globally; no per-file flag customization","Runtime arguments are passed as-is; no shell expansion or variable substitution"],"requires":["Whitelist of allowed compiler flags configured in Judge0","API client capable of specifying flags in submission request","Language compiler supporting the specified flags"],"input_types":["compiler_options string (e.g., '-O2 -Wall')","command_line_arguments string (e.g., 'arg1 arg2')"],"output_types":["compilation output with applied flags","execution results with applied arguments"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_7","uri":"capability://tool.use.integration.webhook.callback.notification.system","name":"webhook-callback-notification-system","description":"Provides webhook callbacks for asynchronous submissions, allowing clients to specify a callback URL that Judge0 will POST to when execution completes. The webhook payload includes the submission token, status, and execution results. The system supports custom headers for authentication (e.g., Bearer tokens) and retries failed webhook deliveries with exponential backoff. This eliminates the need for clients to poll for results.","intents":["I want my platform to be notified when code execution completes without polling","I need to authenticate webhook callbacks to prevent spoofing","I want to handle webhook delivery failures gracefully with retries","I need to integrate Judge0 with my event-driven architecture"],"best_for":["web-based platforms with event-driven architectures","high-volume systems where polling would create excessive load","platforms with real-time user feedback requirements","integration with message queues or event buses"],"limitations":["Webhook endpoint must be publicly accessible; not suitable for client-side-only applications","Webhook delivery is not guaranteed; network failures may result in lost notifications","Retry logic is basic; no dead-letter queue for permanently failed deliveries","Webhook payload size is limited (typically 1MB); large stdout/stderr may be truncated","No built-in webhook signature verification; clients must validate authenticity via custom headers","Webhook delivery latency adds 100-500ms to result notification time"],"requires":["Publicly accessible HTTP endpoint on client side","HTTPS support for secure webhook delivery","Client-side webhook handler capable of processing JSON payloads","Optional: authentication mechanism (Bearer token, API key)"],"input_types":["webhook_url string (HTTPS endpoint)","webhook_headers object (optional authentication headers)"],"output_types":["HTTP POST to webhook_url with JSON payload containing submission token, status, and results"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_8","uri":"capability://data.processing.analysis.language.status.code.interpretation","name":"language-status-code-interpretation","description":"Maps execution outcomes to standardized status codes (Accepted, Wrong Answer, Time Limit Exceeded, Memory Limit Exceeded, Runtime Error, Compilation Error, etc.) that are language-agnostic and consistent across all 60+ supported languages. The system analyzes exit codes, signal information, and execution metrics to determine the appropriate status. This enables clients to provide consistent feedback regardless of the language used.","intents":["I want to show users a consistent 'Time Limit Exceeded' message regardless of language","I need to distinguish between compilation errors and runtime errors automatically","I want to detect out-of-memory errors vs other runtime failures","I need to provide language-agnostic feedback to users"],"best_for":["multi-language competitive programming platforms","educational platforms with diverse language support","assessment systems providing consistent feedback","platforms with language-agnostic user interfaces"],"limitations":["Status code mapping relies on exit codes and signals; some errors may be misclassified","Memory limit detection is approximate; actual OOM may manifest as segmentation fault","Some languages have non-standard error reporting; status codes may be inaccurate","No support for custom status codes; limited to predefined set","Status code interpretation is static; no machine learning or heuristic refinement"],"requires":["Language compiler/interpreter that reports exit codes and signals correctly","Status code mapping configuration for each language"],"input_types":["exit code","signal information","execution metrics (time, memory)"],"output_types":["status code string (e.g., 'Accepted', 'Time Limit Exceeded', 'Runtime Error')","human-readable status description"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-judge0--judge0__cap_9","uri":"capability://safety.moderation.api.authentication.and.authorization","name":"api-authentication-and-authorization","description":"Implements API authentication through API keys or JWT tokens that clients must include in request headers. The system validates credentials against a user/token database in PostgreSQL and enforces rate limiting per authenticated user. Authorization is role-based, allowing operators to restrict certain languages, resource limits, or features to specific users or tiers. The API supports both stateless JWT validation and stateful session-based authentication.","intents":["I want to restrict API access to authenticated users only","I need to implement rate limiting to prevent abuse","I want to offer different feature sets to different user tiers","I need to track API usage per user for billing or analytics"],"best_for":["commercial platforms requiring user authentication","platforms with tiered pricing or feature restrictions","systems requiring audit trails of API usage","multi-tenant platforms isolating user submissions"],"limitations":["Rate limiting is per-user, not per-IP; distributed attacks may bypass limits","No built-in OAuth/SAML support; requires custom integration","JWT tokens have no revocation mechanism; expired tokens must wait for TTL","Authorization is coarse-grained; no fine-grained permission system","No built-in audit logging; API calls are not logged by default"],"requires":["API key or JWT token issued by Judge0 or external auth system","PostgreSQL database for storing user credentials and rate limit state","HTTPS for secure token transmission","Client-side token management and refresh logic"],"input_types":["Authorization header with API key or Bearer token","optional user identifier for rate limiting"],"output_types":["HTTP 401 Unauthorized if authentication fails","HTTP 429 Too Many Requests if rate limit exceeded","HTTP 403 Forbidden if authorization fails"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":47,"verified":false,"data_access_risk":"high","permissions":["Linux kernel 4.4+ with cgroup support for resource limiting","Isolate sandbox system installed and configured on execution worker","PostgreSQL 9.6+ for storing submission metadata and results","Redis 4.0+ for job queue and result caching","60+ language compilers/interpreters installed on worker nodes (gcc, python3, node, etc.)","Language compiler/interpreter binaries installed on worker nodes","Language configuration in Judge0 database (compiler path, execution command template)","Sufficient disk space for compiled artifacts (~100MB per language minimum)","Language-specific runtime libraries (libc, libstdc++, etc.) available on worker","Monitoring system (Prometheus, Datadog, New Relic) for metrics collection"],"failure_modes":["Isolate sandbox is Linux-only; no native Windows/macOS support without virtualization","Resource limit enforcement has ~5-10% variance depending on system load and kernel scheduling","Network access is blocked by default; no outbound HTTP/socket connections from sandboxed code","Execution time limits are wall-clock based, not CPU-time based, affecting multi-threaded code accuracy","File system isolation prevents reading files outside the submission directory","Adding a new language requires installing its compiler/interpreter on all worker nodes","Language versions are fixed per deployment; no per-submission version selection","Some languages have significantly slower startup times (Java ~1-2s vs C++ ~50ms)","Interpreted languages have no compile-time error detection; errors only surface at runtime","No built-in support for language-specific package managers (pip, npm, cargo) for external dependencies","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.5935023297765011,"quality":0.35,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.550Z","last_scraped_at":"2026-05-03T13:57:16.561Z","last_commit":"2026-04-20T17:03:25Z"},"community":{"stars":4144,"forks":856,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=judge0--judge0","compare_url":"https://unfragile.ai/compare?artifact=judge0--judge0"}},"signature":"4+pdX7cEvw4T49YwsiGbuYpPKH/Fs8AYVUu8ia7UnykZFuVtDfbGJrZBFJLrk+2kPQ9awhgnuL+Q1ELIuIl1Dw==","signedAt":"2026-06-20T13:47:41.201Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/judge0--judge0","artifact":"https://unfragile.ai/judge0--judge0","verify":"https://unfragile.ai/api/v1/verify?slug=judge0--judge0","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}