Runsight
YAML-first workflow engine for Git-native AI agents with cost tracking.
A refreshingly practical tool for teams that want to manage AI agents like code. Git-native versioning, granular cost tracking, and local-first execution give you full control—but you'll need to tolerate a steeper learning curve and handle your own infrastructure.
- Developers building multi-step AI agent pipelines
- Teams needing granular cost visibility for agent runs
- Organizations requiring Git-based workflow version control
- Engineers designing evaluation and regression tests for agents
- Non-technical users who prefer no-code only interfaces
- Users needing a fully managed cloud service with zero setup
- Those requiring built-in model hosting or proprietary AI models
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Skip Runsight if you need a plug-and-play no-code agent builder or a managed cloud service—it's a self-hosted YAML-first tool for developers comfortable with Git and local infrastructure.
Your own API key usage costs are not capped by Runsight—only the hard budget caps inside workflows prevent overspend, but you still pay your AI model provider directly.
Runsight is free and open-source (Apache 2.0), so it costs nothing in licensing. It's ideal for cost-conscious developers and startups who already have API keys and infrastructure. Compared to managed alternatives like LangSmith or Semantic Kernel, you save on per-seat fees but trade off convenience and support.
In short
Runsight — YAML-first workflow engine for Git-native AI agents with cost tracking. Best for Developers building multi-step AI agent pipelines, Teams needing granular cost visibility for agent runs, Organizations requiring Git-based workflow version control. Free to use.
Viability Score
How likely is Runsight to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- YAML workflow definitions with versioning
- Git-native version control for workflows
- Per-run cost tracking per block
- Hard budget caps to prevent overspend
- Visual canvas synced with YAML editor
- Monaco YAML editor
- Built-in assertion framework for evaluations
- Pause and kill agent execution mid-run
- Support for loops and sub-workflows
- Block types: linear, gate, code, loop, workflow
- Souls for agent identities (role, prompt, model, tools)
- Custom tool definitions (HTTP, Python, file-based)
- Self-hosted with your own API keys
- Real-time execution trace with cost and latency
- No vendor lock-in (Apache 2.0)
About Runsight
Runsight is an open-source, YAML-first workflow engine for building and managing AI agent pipelines. You define agent workflows as YAML files that live in Git repositories, enabling version control, code review, and collaboration on agent behavior. The tool provides a visual canvas that stays bidirectionally synced with a Monaco YAML editor—drag nodes or edit code, the other view updates instantly. Every run is traced per block with cost and latency, and hard budget caps prevent overspend, making it ideal for teams that need transparency and control over agent operations. Runsight is self-hosted, runs with your own API keys and models, and is fully open-source under Apache 2.0, avoiding vendor lock-in. It's designed for developers and teams building complex multi-step agent workflows, especially those already using Git for code management.
Behind the Verdict
Runsight hits a sweet spot for teams that treat AI agent pipelines as software artifacts. If you're already deep in Git workflows and need cost transparency per run, this is a no-nonsense pick. The YAML-first approach means your workflow configs are version-controlled and diffable, which plays nicely with code review processes. The visual canvas synced with the YAML editor is a nice touch for debugging complex pipelines. Where it bites: onboarding requires comfort with the command line (uvx runsight) and a willingness to self-host. Non-technical users will struggle. Compared to alternatives like LangChain or Haystack, Runsight is less about pre-built integrations and more about giving you a structured way to define and trace your own multi-step agent logic. There's no managed cloud, so you're responsible for uptime and scaling. But for teams that prioritize control and cost tracking over convenience, it's a solid bet.
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Real-world workflow fit
Concrete scenarios for the personas Runsight actually fits — and what changes day-one when you adopt it.
You create a YAML workflow with research and review blocks, assign souls with different models (e.g., GPT-5.5 for research, Claude Opus 4.7 for review), and set a $2 budget cap.
Outcome: The agent runs end-to-end in under 10 seconds, cost tracked at $0.05 total, with the ability to pause mid-run if needed.
You commit a workflow YAML to your repo, a colleague reviews and merges a change to the soul definition via a pull request, then runs the updated workflow.
Outcome: Workflow changes are versioned, reviewed, and runnable directly—no config drift or manual syncing.
Use Cases
- Define and version AI agent workflows as YAML files in your Git repository.
- Track per-run costs for each block in a multi-step agent pipeline.
- Set hard budget caps to automatically halt execution if spending exceeds limits.
- Pause a running agent, inspect its state, and then resume or kill execution.
- Use built-in assertions to validate block outputs and run regression tests across workflows.
Models Under the Hood
as of 2026-07-17
Limitations
- Runsight is self-hosted and requires users to manage their own API keys and infrastructure.
- It does not provide a managed cloud service, and current integrations are limited to custom tools defined in YAML.
- The tool's feature set is focused on workflow orchestration rather than model hosting or training.
as of 2026-07-03
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Runsight tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source
$0
Where the pricing makes sense
The company stage and team size where Runsight's pricing actually pencils out — and where peers do it cheaper.
Runsight is free and open-source (Apache 2.0), so it costs nothing in licensing. It's ideal for cost-conscious developers and startups who already have API keys and infrastructure. Compared to managed alternatives like LangSmith or Semantic Kernel, you save on per-seat fees but trade off convenience and support.
Setup time & first value
How long it actually takes to get something useful out of Runsight — broken out by persona, not the marketing-page minute.
For a solo developer familiar with YAML and the terminal: first run in under 5 minutes using `uvx runsight`. Adding API keys and building a simple two-block workflow takes about 15 minutes. For teams version-controlling workflows in Git, expect an hour to onboard a new member and set up review practices.
Resources & Guides
Official links
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