{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"temporal","slug":"temporal","name":"Temporal","type":"framework","url":"https://github.com/temporalio/temporal","page_url":"https://unfragile.ai/temporal","categories":["automation"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"temporal__cap_0","uri":"capability://automation.workflow.durable.workflow.execution.with.automatic.state.recovery","name":"durable workflow execution with automatic state recovery","description":"Executes workflow code as a series of deterministic steps with automatic state persistence and recovery. Uses event sourcing via the History Service to store all workflow decisions and events in an immutable event log, enabling workers to replay execution history and recover from failures without re-executing completed steps. The Mutable State Management system tracks workflow progress across shards, and the History Engine reconstructs state by replaying events up to the failure point.","intents":["I need my workflow to survive worker crashes and network failures without losing progress or re-running completed tasks","I want to understand exactly what happened in a workflow execution by inspecting its complete event history","I need to resume a workflow from the exact point it failed, not from the beginning"],"best_for":["teams building distributed systems with strict reliability requirements","AI agent pipelines requiring guaranteed task completion across infrastructure failures","financial or payment processing systems where idempotency and auditability are critical"],"limitations":["Workflow code must be deterministic — non-deterministic operations (random, timestamps, external calls) must be wrapped in Activities, adding complexity","Event log grows unbounded over time; requires periodic archival or compaction to manage storage costs","Replaying large event histories can add latency (100ms-1s per 1000 events depending on complexity)","State reconstruction is synchronous and blocks workflow task processing until complete"],"requires":["Persistent storage backend (PostgreSQL, MySQL, Cassandra, or DynamoDB)","Worker process with Temporal SDK (Go, Java, Python, TypeScript, .NET)","gRPC connectivity between workers and Temporal server","Deterministic workflow code (no random, no direct external I/O)"],"input_types":["workflow definition (code)","workflow input parameters (JSON-serializable objects)","event history (internal, managed by Temporal)"],"output_types":["workflow result (JSON-serializable)","event history log (immutable sequence of WorkflowExecutionStarted, ActivityTaskScheduled, ActivityTaskCompleted, etc.)","execution state snapshot (for debugging)"],"categories":["automation-workflow","distributed-systems"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_1","uri":"capability://tool.use.integration.activity.based.external.service.integration.with.automatic.retries.and.timeouts","name":"activity-based external service integration with automatic retries and timeouts","description":"Wraps external service calls (HTTP APIs, database queries, ML model inference) as Activities — isolated, non-deterministic operations that run on workers and report results back to the workflow. The Matching Service routes activity tasks to available workers via task queues, and the History Service tracks activity completion. Built-in retry policies (exponential backoff, max attempts, jitter) and timeout enforcement (start-to-close, schedule-to-start, heartbeat) are applied automatically without workflow code changes.","intents":["I need to call external APIs from my workflow with automatic retries and timeout protection","I want to parallelize multiple external calls and wait for all results before proceeding","I need to detect if an external service is hanging and fail fast instead of waiting indefinitely"],"best_for":["workflows integrating with third-party APIs (payment processors, ML services, data warehouses)","AI agent pipelines calling LLM APIs, vector databases, or tool services","teams needing fine-grained control over retry behavior per activity type"],"limitations":["Activities must be idempotent — Temporal may retry them multiple times, so side effects must be safe to repeat","Heartbeat mechanism requires activity code to periodically call heartbeat() to prove liveness; missing heartbeats trigger timeout","Activity results are serialized/deserialized (JSON by default), adding overhead for large payloads (>1MB)","No built-in circuit breaker — cascading failures to external services require manual implementation in activity code"],"requires":["Activity implementation in Temporal SDK (Go, Java, Python, TypeScript, .NET)","Task queue configured on workers to receive activity tasks","Network connectivity from workers to external services","Idempotent external service calls (or idempotency tokens)"],"input_types":["activity parameters (JSON-serializable)","context with timeout and retry metadata"],"output_types":["activity result (JSON-serializable)","activity error with retry decision (retry, fail, or timeout)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_10","uri":"capability://automation.workflow.archival.and.long.term.retention.of.workflow.history","name":"archival and long-term retention of workflow history","description":"Automatically archives completed workflow histories to a long-term storage backend (S3, GCS, or database) after a retention period. The Archiver Service runs as a background process and moves histories from the main event log to archive storage, freeing up database space. Archived histories can be retrieved via the Temporal API for auditing or compliance purposes, though with higher latency than active histories.","intents":["I need to keep workflow histories for compliance (7 years for financial records) without bloating the main database","I want to query historical workflows from years ago for auditing purposes","I need to reduce database storage costs by archiving old workflow data"],"best_for":["regulated industries (finance, healthcare) with long retention requirements","systems with high workflow volume and limited database storage","compliance and audit systems requiring historical data access"],"limitations":["Archived histories are not queryable via the Visibility Store; require direct archive access","Archival is asynchronous and may lag behind workflow completion by hours or days","Retrieving archived histories requires separate API calls and is slower than active histories","Archive storage costs (S3, GCS) can be significant for high-volume systems; requires cost monitoring"],"requires":["Archive storage backend (S3, GCS, or database)","Archiver Service running and configured","Retention policy (how long to keep histories in main database)"],"input_types":["retention period (duration)","archive storage configuration"],"output_types":["archived workflow history (in archive storage)","retrieval API for accessing archived histories"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_11","uri":"capability://safety.moderation.metrics.and.observability.with.structured.logging.and.tracing","name":"metrics and observability with structured logging and tracing","description":"Emits detailed metrics (latency, throughput, error rates) and structured logs for all Temporal operations. Metrics are tagged with service, operation, and namespace for fine-grained analysis. The system integrates with OpenTelemetry for distributed tracing, enabling end-to-end visibility of workflow execution across services. Metrics are exported to monitoring systems (Prometheus, Datadog, CloudWatch) via configurable exporters.","intents":["I need to monitor workflow execution latency and identify performance bottlenecks","I want to track error rates and failure reasons to improve reliability","I need to trace a specific workflow execution across all Temporal services to debug issues"],"best_for":["operations teams monitoring production Temporal clusters","developers debugging workflow performance issues","SREs building dashboards and alerts for Temporal health"],"limitations":["Metrics cardinality can explode with high-cardinality tags (e.g., workflow ID); requires careful tag design","Tracing adds overhead (5-10% latency increase); should be sampled in high-throughput systems","Metrics are emitted asynchronously; brief delays before data appears in monitoring systems","No built-in alerting; requires external monitoring system (Prometheus, Datadog) to define alerts"],"requires":["Metrics exporter configured (Prometheus, Datadog, CloudWatch, etc.)","Monitoring system to scrape/ingest metrics","OpenTelemetry SDK (optional, for distributed tracing)"],"input_types":["metrics configuration (exporter type, endpoint)","tracing configuration (sampling rate, exporter)"],"output_types":["metrics (latency, throughput, error rates, task queue depth)","structured logs (JSON format with context)","distributed traces (OpenTelemetry format)"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_12","uri":"capability://tool.use.integration.nexus.operations.for.cross.workflow.and.cross.cluster.communication","name":"nexus operations for cross-workflow and cross-cluster communication","description":"Enables workflows in one cluster to invoke operations (workflows or activities) in another cluster or namespace via the Nexus protocol. Nexus operations are asynchronous and return a handle that can be awaited for results. The Frontend Service routes Nexus requests to the target cluster, and the History Service tracks the async operation. This enables federated workflow systems where workflows can span multiple clusters.","intents":["I need to invoke a workflow in another Temporal cluster from my workflow","I want to call a shared service workflow (e.g., payment processing) from multiple workflows across clusters","I need to build a federated workflow system where workflows can span multiple datacenters"],"best_for":["multi-cluster deployments with shared services","federated AI agent systems where agents can invoke services across clusters","organizations with separate Temporal clusters per region needing cross-region communication"],"limitations":["Nexus operations add latency (network round-trip to target cluster); not suitable for latency-sensitive operations","Nexus operations are asynchronous; synchronous request-response patterns require explicit await","Cross-cluster communication requires network connectivity and authentication; adds operational complexity","Nexus protocol is relatively new; less mature than local workflow calls"],"requires":["Nexus endpoint configured in target cluster","Network connectivity between clusters","Authentication/authorization for cross-cluster calls","Nexus operation definition in target cluster"],"input_types":["Nexus operation name (string)","operation input (JSON-serializable)"],"output_types":["Nexus operation handle (async)","operation result (when awaited)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_13","uri":"capability://automation.workflow.dynamic.configuration.and.feature.flags.for.runtime.behavior.control","name":"dynamic configuration and feature flags for runtime behavior control","description":"Enables runtime configuration changes without restarting the Temporal server via a dynamic configuration system. Configuration values (timeouts, quotas, feature flags) are stored in the database and polled by services at regular intervals. Changes take effect within seconds. The system supports per-namespace and per-workflow-type overrides, enabling fine-grained control.","intents":["I need to adjust timeout values or quotas without restarting the Temporal server","I want to enable/disable features (e.g., workflow versioning) for specific namespaces","I need to roll out a feature gradually using feature flags"],"best_for":["operations teams managing production Temporal clusters","feature rollout and canary testing","tuning system behavior in response to production issues"],"limitations":["Configuration changes are eventually consistent; brief windows exist where different services have different config values","No built-in validation; invalid configuration values can cause errors","Configuration changes are not audited; requires external logging to track who changed what","Polling-based updates add latency (typically 1-5 seconds) before changes take effect"],"requires":["Dynamic configuration system configured and running","Database backend for storing configuration","Admin API access to update configuration"],"input_types":["configuration key (string)","configuration value (type-specific: duration, integer, boolean, string)","optional namespace or workflow-type override"],"output_types":["configuration update acknowledgment","current configuration value"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_14","uri":"capability://automation.workflow.scheduler.workflow.for.recurring.and.delayed.execution","name":"scheduler workflow for recurring and delayed execution","description":"Provides a built-in Scheduler Workflow that enables recurring workflow execution (cron-like schedules) and delayed execution without requiring external schedulers. Schedules are defined with cron expressions or interval-based patterns, and the Scheduler Workflow automatically spawns workflow executions at the scheduled times. Supports timezone-aware scheduling, backfill for missed executions, and pause/resume of schedules.","intents":["Execute workflows on a recurring schedule (daily, weekly, monthly) without external cron jobs","Delay workflow execution until a specific time without blocking the caller","Implement backfill for missed executions if the scheduler was temporarily unavailable","Manage schedules via API without requiring code deployment"],"best_for":["systems with recurring workflows (daily reports, weekly cleanups, monthly billing)","teams wanting to eliminate external cron job dependencies","applications needing timezone-aware scheduling"],"limitations":["Scheduler Workflow is a system workflow; failures can impact all schedules in a namespace","Cron expression parsing is limited to standard cron syntax; complex schedules require custom logic","Backfill is not automatic; requires explicit configuration and can cause thundering herd if many executions are backfilled","Timezone handling requires explicit configuration; daylight saving time transitions can cause missed executions"],"requires":["Scheduler Workflow deployed in the namespace","Schedule definition (cron expression or interval)","Temporal server with Scheduler Workflow support"],"input_types":["schedule ID (string)","cron expression (string, e.g., '0 9 * * MON')","workflow type and input parameters"],"output_types":["schedule status (active, paused, deleted)","next execution time (timestamp)","recent executions (list of workflow IDs)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_2","uri":"capability://automation.workflow.task.queue.based.worker.load.balancing.and.versioning","name":"task queue-based worker load balancing and versioning","description":"Routes workflow and activity tasks to workers via named task queues managed by the Matching Service. Workers poll task queues and execute tasks; the Matching Service maintains a registry of available workers per queue and distributes tasks fairly. Worker Versioning enables gradual rollouts: new worker versions are tagged, and the server can route tasks to specific versions or gradually shift traffic from old to new versions, enabling zero-downtime deployments.","intents":["I need to scale workers independently for different workflow types without deploying a monolithic service","I want to deploy a new version of my workflow code without stopping in-flight executions","I need to route high-priority tasks to dedicated workers while other tasks share a pool"],"best_for":["teams running multiple workflow types with different resource requirements (CPU, memory, latency)","organizations with strict deployment policies requiring gradual rollouts and canary testing","AI agent systems where different agent types (planning, execution, monitoring) need separate worker pools"],"limitations":["Task queue names are static at workflow start time; cannot dynamically route a running workflow to a different queue","Worker versioning requires explicit version tags in code; no automatic version detection","Matching Service becomes a bottleneck under extreme load (>100k tasks/sec); requires horizontal scaling and careful tuning","No built-in priority queue — all tasks in a queue are processed FIFO; priority requires separate queues"],"requires":["Named task queue configured in workflow definition","Worker process polling the task queue (via Temporal SDK)","Matching Service running and healthy","Worker versioning requires SDK support (available in Go, Java, Python, TypeScript)"],"input_types":["task queue name (string)","worker version tag (optional, string)"],"output_types":["task dispatch decision (route to specific worker version or pool)","task execution result"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_3","uri":"capability://automation.workflow.workflow.update.and.signal.handling.for.runtime.state.changes","name":"workflow update and signal handling for runtime state changes","description":"Allows external systems to send Signals (asynchronous notifications) and Updates (synchronous requests with responses) to running workflows without stopping them. Signals are queued and processed by the workflow at safe points; Updates block the caller until the workflow processes the request and returns a result. The History Service records all signals and updates in the event log, ensuring they survive worker failures and are replayed correctly.","intents":["I need to pause or cancel a long-running workflow from an external API call","I want to send configuration changes to a running workflow without restarting it","I need to query a workflow for its current state and get a synchronous response"],"best_for":["interactive workflows that respond to user actions (approval workflows, interactive agents)","long-running processes that need runtime configuration updates (batch jobs, monitoring tasks)","AI agents that need to accept user feedback or interrupts during execution"],"limitations":["Signals are asynchronous and may be processed out of order if multiple signals are sent rapidly","Updates require the workflow to explicitly handle them in code; no default behavior","Signal/Update handlers must be deterministic (same as workflow code); non-deterministic operations must use Activities","No built-in rate limiting on signals; high-frequency signal storms can overwhelm the workflow"],"requires":["Workflow code with signal/update handlers defined","External client with Temporal SDK to send signals/updates","Running workflow instance (cannot send signals to completed workflows)"],"input_types":["signal name (string)","signal payload (JSON-serializable)","update name (string)","update request (JSON-serializable)"],"output_types":["signal acknowledgment (async, no return value)","update response (JSON-serializable, synchronous)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_4","uri":"capability://automation.workflow.cross.datacenter.replication.and.failover.for.disaster.recovery","name":"cross-datacenter replication and failover for disaster recovery","description":"Replicates workflow state and history across multiple datacenters using the Replication System. The History Service streams events to replica clusters in near-real-time; if the primary cluster fails, clients can failover to a replica cluster and resume workflows. Namespace-level replication policies control which clusters receive updates and in what order, enabling active-passive or active-active topologies.","intents":["I need my workflows to survive a complete datacenter outage without losing state","I want to replicate workflows to a geographically distant cluster for disaster recovery","I need to failover to a backup cluster with minimal data loss and downtime"],"best_for":["mission-critical systems (financial services, healthcare) with strict RTO/RPO requirements","globally distributed applications needing local failover clusters","teams with multi-region deployment strategies"],"limitations":["Replication adds latency (50-500ms depending on network distance) to workflow execution","Failover is not automatic; requires manual intervention or external orchestration to switch clients to replica cluster","Replication is eventually consistent; brief windows exist where primary and replica are out of sync","Requires separate Temporal cluster infrastructure in each datacenter, multiplying operational complexity","No built-in conflict resolution for active-active topologies; requires careful namespace configuration"],"requires":["Multiple Temporal clusters (primary + 1+ replicas)","Network connectivity between clusters (gRPC)","Namespace configured with replication policy","Persistent storage in each cluster (PostgreSQL, MySQL, Cassandra, DynamoDB)"],"input_types":["replication policy (namespace configuration)","failover target cluster (client configuration)"],"output_types":["replicated event log (in replica cluster)","failover status (primary healthy, replica active, etc.)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_5","uri":"capability://automation.workflow.namespace.isolation.and.multi.tenancy.with.resource.quotas","name":"namespace isolation and multi-tenancy with resource quotas","description":"Partitions workflows, activities, and task queues into isolated namespaces, enabling multi-tenant deployments. Each namespace has its own event history, visibility store, and configuration. The Frontend Service enforces namespace isolation via request interceptors, and dynamic configuration enables per-namespace quotas (max concurrent workflows, max task queue depth, rate limits). Namespaces can be replicated independently, supporting per-tenant disaster recovery policies.","intents":["I need to run workflows for multiple customers in a single Temporal cluster without cross-contamination","I want to enforce resource limits per customer (max concurrent workflows, max API calls)","I need to replicate some customer workflows to a backup cluster while others stay local"],"best_for":["SaaS platforms offering workflow automation as a service","multi-tenant AI agent platforms with per-customer resource limits","enterprises with multiple business units needing isolated workflow environments"],"limitations":["Namespace isolation is logical, not cryptographic; requires trust in the Temporal operator","Cross-namespace queries are not supported; requires separate API calls per namespace","Quota enforcement is soft (advisory) not hard; exceeding quotas triggers warnings but does not block execution","Namespace deletion is not reversible; requires careful planning for long-term data retention"],"requires":["Namespace created via Temporal CLI or API","Dynamic configuration system (for quota management)","Client code specifying namespace in connection parameters"],"input_types":["namespace name (string)","namespace configuration (retention, replication policy, quotas)"],"output_types":["namespace isolation boundary (enforced by Frontend Service)","quota enforcement decision (allow or warn)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_6","uri":"capability://search.retrieval.workflow.visibility.and.querying.with.sql.like.search","name":"workflow visibility and querying with sql-like search","description":"Indexes workflow executions in a Visibility Store (separate from the main event log) with searchable fields (workflow type, status, start time, custom attributes). The Frontend Service exposes a ListWorkflowExecutions API that supports SQL-like queries (e.g., 'WorkflowType = \"payment\" AND Status = RUNNING AND StartTime > now - 1h'). Visibility data is eventually consistent with the main event log, updated asynchronously by the Worker Service.","intents":["I need to find all running workflows of a specific type to monitor progress","I want to search for workflows by custom attributes (customer ID, order ID) to debug issues","I need to generate reports on workflow execution metrics (success rate, duration, failure reasons)"],"best_for":["operational dashboards and monitoring systems","debugging and troubleshooting workflows in production","compliance and audit systems requiring searchable execution records"],"limitations":["Visibility queries are eventually consistent (lag of 1-5 seconds typical); not suitable for real-time decision-making","Custom attributes must be explicitly set in workflow code; no automatic extraction","Query performance degrades with large result sets (>10k workflows); requires pagination","Visibility Store is separate from event log; requires dual writes and eventual consistency handling"],"requires":["Visibility Store backend (Elasticsearch, OpenSearch, or database-specific implementation)","Workflow code setting custom attributes via SetSearchAttributes()","Frontend Service configured with Visibility Store connection"],"input_types":["SQL-like query string","pagination parameters (page size, token)"],"output_types":["list of workflow execution summaries (ID, type, status, start time, custom attributes)","pagination token for next page"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_7","uri":"capability://automation.workflow.workflow.versioning.and.code.evolution.without.breaking.in.flight.executions","name":"workflow versioning and code evolution without breaking in-flight executions","description":"Enables safe code changes to workflows via versioning primitives (GetVersion() API) that allow workflows to execute different code paths based on version. When workflow code changes, new executions use the new code, while in-flight executions continue with the old code path until they complete. The History Service replays events with the correct version context, ensuring determinism. This eliminates the need to wait for all in-flight executions to complete before deploying.","intents":["I need to deploy a new version of my workflow code without waiting for all running workflows to finish","I want to gradually migrate workflows from old to new code paths without breaking in-flight executions","I need to roll back a workflow code change without losing execution state"],"best_for":["teams with frequent workflow code deployments and long-running executions","AI agent systems evolving agent logic while maintaining in-flight agent instances","systems requiring zero-downtime deployments"],"limitations":["Requires explicit GetVersion() calls in workflow code; not automatic","Version history grows over time; old version code paths must be maintained for backward compatibility","Rollback requires manual code changes; no automatic version revert","Complex version logic can make workflow code harder to understand and maintain"],"requires":["Workflow code using GetVersion() API to branch on version","Version number incremented in code for each breaking change","Old code paths maintained for backward compatibility"],"input_types":["version number (integer)","version-specific code path"],"output_types":["execution result using correct version code path"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_8","uri":"capability://automation.workflow.scheduler.workflow.for.recurring.and.delayed.task.execution","name":"scheduler workflow for recurring and delayed task execution","description":"Provides a built-in Scheduler Workflow that executes other workflows on a schedule (cron-like) or with a delay. The Scheduler Workflow runs continuously and spawns child workflows at specified intervals or times. Schedules are stored in the Temporal database and survive server restarts. The Worker Service manages schedule execution, ensuring that missed schedules are caught up when the server recovers.","intents":["I need to run a workflow every hour or on a cron schedule without external schedulers like cron or Kubernetes CronJob","I want to delay a workflow execution by a specific duration (e.g., retry after 5 minutes)","I need to manage schedules dynamically (create, update, delete) via API without redeploying"],"best_for":["batch processing jobs (daily reports, data cleanup, reconciliation)","retry logic with exponential backoff delays","AI agent systems with periodic tasks (model retraining, cache refresh)"],"limitations":["Schedule precision is limited by the Scheduler Workflow polling interval (typically 1 second); not suitable for sub-second precision","Missed schedules are caught up sequentially; if the server is down for 1 hour, 60 workflows will be spawned in rapid succession","No built-in timezone support; schedules are in UTC","Schedule management requires API calls; no UI for schedule creation"],"requires":["Scheduler Workflow running on a dedicated task queue","Target workflow definition (the workflow to be scheduled)","Schedule specification (cron expression or delay duration)"],"input_types":["schedule specification (cron string or delay duration)","workflow type and input parameters"],"output_types":["spawned workflow execution (ID, status)","schedule execution history"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__cap_9","uri":"capability://automation.workflow.batch.operations.for.bulk.workflow.management","name":"batch operations for bulk workflow management","description":"Provides batch APIs to perform operations on multiple workflows in bulk: cancel, terminate, or signal multiple workflows matching a query. The Frontend Service processes batch requests by querying the Visibility Store for matching workflows and then issuing individual operations. Batch operations are asynchronous and return a job ID for tracking progress.","intents":["I need to cancel all running workflows of a specific type due to a bug or outage","I want to send a signal to all workflows matching a query (e.g., all workflows for a customer)","I need to terminate workflows that have been running longer than expected"],"best_for":["operational tasks (bulk cancellation, bulk signaling)","disaster recovery (terminating workflows affected by an outage)","maintenance operations (bulk state updates via signals)"],"limitations":["Batch operations are asynchronous; no guarantee of atomicity across all matched workflows","Query-based matching uses the Visibility Store, which is eventually consistent; some workflows may be missed","No rollback mechanism; if a batch operation fails partway through, manual cleanup may be required","Large batch operations (>100k workflows) can overwhelm the server; requires careful rate limiting"],"requires":["Visibility Store with searchable workflows","Batch operation API (cancel, terminate, signal)","Query matching the workflows to operate on"],"input_types":["query string (SQL-like)","operation type (cancel, terminate, signal)","operation parameters (e.g., signal name and payload)"],"output_types":["batch job ID","batch operation status (in progress, completed, failed)","count of affected workflows"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"temporal__headline","uri":"capability://automation.workflow.durable.workflow.orchestration.framework","name":"durable workflow orchestration framework","description":"Temporal is a durable execution platform designed for building reliable distributed systems, providing workflow-as-code capabilities with automatic retries, timeouts, and state management, making it ideal for complex AI agent pipelines.","intents":["best workflow orchestration framework","workflow orchestration for distributed systems","how to implement durable workflows","reliable workflow management tools","scalable workflow solutions for AI"],"best_for":["developers building distributed systems","teams needing reliable workflow management"],"limitations":["requires understanding of workflow design patterns"],"requires":["basic knowledge of distributed systems"],"input_types":["code workflows"],"output_types":["executed workflows","workflow state management"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":57,"verified":false,"data_access_risk":"high","permissions":["Persistent storage backend (PostgreSQL, MySQL, Cassandra, or DynamoDB)","Worker process with Temporal SDK (Go, Java, Python, TypeScript, .NET)","gRPC connectivity between workers and Temporal server","Deterministic workflow code (no random, no direct external I/O)","Activity implementation in Temporal SDK (Go, Java, Python, TypeScript, .NET)","Task queue configured on workers to receive activity tasks","Network connectivity from workers to external services","Idempotent external service calls (or idempotency tokens)","Archive storage backend (S3, GCS, or database)","Archiver Service running and configured"],"failure_modes":["Workflow code must be deterministic — non-deterministic operations (random, timestamps, external calls) must be wrapped in Activities, adding complexity","Event log grows unbounded over time; requires periodic archival or compaction to manage storage costs","Replaying large event histories can add latency (100ms-1s per 1000 events depending on complexity)","State reconstruction is synchronous and blocks workflow task processing until complete","Activities must be idempotent — Temporal may retry them multiple times, so side effects must be safe to repeat","Heartbeat mechanism requires activity code to periodically call heartbeat() to prove liveness; missing heartbeats trigger timeout","Activity results are serialized/deserialized (JSON by default), adding overhead for large payloads (>1MB)","No built-in circuit breaker — cascading failures to external services require manual implementation in activity code","Archived histories are not queryable via the Visibility Store; require direct archive access","Archival is asynchronous and may lag behind workflow completion by hours or days","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.3,"quality":0.2,"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":"2026-06-17T09:51:05.296Z","last_scraped_at":null,"last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=temporal","compare_url":"https://unfragile.ai/compare?artifact=temporal"}},"signature":"pZ7lKRE0XLUK6uu7cYF7mg86FGvNKjf5kpCkUgVajVDxpb4JHYcQCpAdXsqpyrjBT+qwpkrfS/nxj39T2DzcCw==","signedAt":"2026-06-22T11:44:44.538Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/temporal","artifact":"https://unfragile.ai/temporal","verify":"https://unfragile.ai/api/v1/verify?slug=temporal","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"}}