Openagentskill vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionOpenagentskillTemporal AI
PricingFreeFreemium (cloud with usage-based billing, self-hosted free)
Primary FunctionSkill registry & discovery for AI agentsDurable execution & workflow orchestration
DeploymentCLI & API (no runtime)Cloud or self-hosted
Key IntegrationCodex, Claude Code, Cursor, MCPOpenAI Agents SDK, Google ADK, Slack, Kubernetes
Best ForDiscovering & installing agent skillsReliable, stateful workflows with retries
Target UsersAI agent developers & DevOpsDevelopers building resilient systems

If you need durable, crash-proof execution for multi-step AI workflows or microservices, Temporal is the clear choice—its state capture and recovery features are unmatched. If your main goal is to discover, audit, and install reusable agent skills from a registry, OpenAgentSkill offers a free, purpose-built solution without orchestration overhead. Choose Temporal for reliability, choose OpenAgentSkill for skill discovery.

Openagentskill
Openagentskill

Give your AI agent a job in plain language and OpenAgentSkill hands back one ranked, install-ready skill with trust signals attached.

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Temporal AI
Temporal AI

Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.

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Pricing
Free
Freemium
Plans
—
$150 credits for 90 days
Starting at $50 per million actions
Greater of $500/mo or 10% of usage
Custom
Popularity
10 views
7.5k views
Skill Level
Intermediate
Advanced
API Available
Platforms
APICLIWeb
WebAPI
Categories
🕸️ Agent Frameworks & Orchestration🔌 MCP Servers & Agent Tooling
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
Features
Natural-language task-to-skill resolution via POST /api/agent/resolve
Returns one recommended skill plus ranked alternatives with fit scores
Trust profiles with risk summaries, permission hints and readiness notes
Install plan generation with ready-to-run npx commands
GET /api/agent/skills/{name} for repository health and risk review
GET /api/skills/{name}/install?format=text tuned for low-token LLM calls
format=text responses across skill list and search endpoints
Works with Codex, Claude Code, Cursor, MCP-compatible agents and custom runtimes
npx CLI with a --dry-run resolve step before anything is installed
Copy for AI flow that pastes a prompt into Codex, Claude Code or Cursor without installing
GitHub popularity leaderboard filtering weak matches before ranking
Ranking across workflow fit, maintenance activity, GitHub stars and audit signals
Human browsing by category and by output format alongside the agent API
Gallery of skills with published author example outputs
Skill submission via GitHub with a SKILL.md name and description manifest
Durable execution captures Workflow state at every step with no checkpointing or recovery code
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Activities retry automatically with backoff, four timeout classes, and heartbeating
Signals, Queries, and Updates read and mutate running Workflows mid-flight
Workflow Streams for real-time interactivity with running executions
Durable AI agents via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities
Serverless Workers host durable AI agents on Amazon Bedrock AgentCore
Serverless Workers on AWS Lambda (public preview) and GCP Cloud Run (pre-release)
Standalone Activities as a durable job-queue pattern, GA across six SDKs (2026-09-15)
Native Task Queue priority and fair distribution without a custom queueing layer
Durable Timers sleep for months; cron Schedules support backfill and Continue-As-New
Saga pattern via compensating transactions that read like try/catch
Worker Versioning pins Workflows to a version so deploys don't corrupt in-flight runs
Cloud UI Strict Session Mode enforces 15-min inactivity timeout and 12-hour max session (GA 2026-09-18)
Replay tests validate against real histories; time-skipping tests fast-forward long timers in CI
Integrations
GitHub
Codex
Claude Code
Cursor
MCP
OpenAI Agents SDK
Google ADK
AWS Lambda
Google Cloud Run
Amazon Bedrock AgentCore
Kubernetes
GitHub Actions
GCP Marketplace
Azure

What real users say: Openagentskill vs Temporal AI

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Openagentskill

17 mentions across 2 sources · 70% positive (averaged across 2 sources)

YouTube, GitHub

What users praise

  • • Agent-first design with natural language task-to-skill resolution.
  • • Trust profiles with risk, permissions, and audit notes for safety.
  • • Install plans generate ready-to-run commands for multiple surfaces.
  • • Web, API, and CLI access make it flexible for any workflow.

What frustrates them

  • • Approved submissions not persisted when database save fails.
  • • Security risk: agent might install every skill without oversight.
  • • Privacy: anonymous telemetry may concern sensitive users.
  • • Limited real-world feedback on reliability in production.

Researched Aug 1, 2026

Temporal AI

No verifiable community signal. We scanned public discussion on Oct 14, 2026 and found posts matching the name “Temporal AI”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

Who should pick which

  • Developer building AI agents
    Pick: Temporal AI

    Temporal provides durable execution so agents survive crashes; integrates with OpenAI Agents SDK and Google ADK.

  • DevOps engineer automating workflows
    Pick: Temporal AI

    Temporal supports retries, Saga pattern, and integrates with Kubernetes for CI/CD orchestration.

  • AI agent researcher exploring skills
    Pick: Openagentskill

    OpenAgentSkill offers free access to 20K+ skills with audit trails and install commands for rapid prototyping.

  • Startup building a custom agent runtime
    Pick: Openagentskill

    OpenAgentSkill's API-driven skill index integrates with Codex, Claude Code, and MCP agents for seamless discovery.

  • Fintech team needing compensation transactions
    Pick: Temporal AI

    Temporal's Saga pattern and human-in-the-loop features ensure transactional integrity and manual approval steps.

Frequently Asked Questions

Openagentskill vs Temporal AI: which should you choose?

If you need durable, crash-proof execution for multi-step AI workflows or microservices, Temporal is the clear choice—its state capture and recovery features are unmatched. If your main goal is to discover, audit, and install reusable agent skills from a registry, OpenAgentSkill offers a free, purpose-built solution without orchestration overhead. Choose Temporal for reliability, choose OpenAgentSkill for skill discovery.

Can OpenAgentSkill execute workflows?

No, OpenAgentSkill is only a registry for discovering and installing skills. It does not provide execution or orchestration.

Does Temporal support AI agent integrations?

Yes, Temporal integrates with OpenAI Agents SDK, Google ADK, and others for building reliable AI agents.

Is Temporal free to use?

The open-source server is free. Temporal Cloud uses usage-based billing, with improved cost transparency added in June 2026.

What integrations does OpenAgentSkill offer?

It integrates with Codex, Claude Code, Cursor, MCP-compatible agents, and GitHub.

Which tool is better for long-running workflows?

Temporal is built for durable, long-running processes with state persistence and automatic recovery.

Can I use OpenAgentSkill for skill safety?

Yes, it provides trust profiles with risk summaries, permissions, and audit notes to evaluate skills.

Does Temporal support human-in-the-loop?

Yes, via signals, pause/resume, and human-in-the-loop capabilities.

Which tool has a larger community?

Temporal is used by OpenAI, Replit, and Cursor, and has significant adoption. OpenAgentSkill has 860K+ downloads across 104 agent surfaces.

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Last reviewed: July 3, 2026