Open source agentic coding harness, optimized for difficulty aware multi-model execution layer workflows. A @morganlinton invention 💡albatross.shJoined April 2024
Just shipped Albatross v2.3.0 🪽
This release came directly from user feedback provided by @danielendara, so thank you Daniel!
He brought up a lot of good stuff, here's what's new:
- cleaner long-prompt wrapping
- familiar Enter-to-select commands
- /provider terminology
- four terminal themes.
- guided /route experience
- bugfix for ChatGPT integration so GPT‑5.6 Sol, Terra, and Luna are now available
brew update && brew upgrade albatross
@BlockedPaths@morganlinton@yuppieventures Well you can technically add it in, but I'd get in legal trouble, I need to actually connect with Anthropic directly, fill out paperwork, etc.
Just shipped Albatross v2.2.0 🪽
Anthropic is now a first-class Albatross provider.
You can bring an ANTHROPIC_API_KEY and use Claude through Anthropic’s documented Messages and Models APIs, with native streaming, tool calls, image inputs, extended-thinking signature round-tripping, model-aware effort controls, and cache-aware token and cost accounting.
And because routing transparency has always been central to Albatross, Anthropic runs get the same inspectable goodness: which model was requested and resolved, which effort level was requested and actually used, input/output/cache tokens, latency, pricing source, and estimated cost.
One boundary I want to be explicit about: this release does not reuse Claude.ai or Claude Code credentials, and it does not turn a Pro or Max subscription into third-party API access.
I’d love to support subscription OAuth, but only through an approved path, so I'll need to wait to get the greenlight from Anthropic.
For now, v2.2.0 takes the safe path: the official API, your key, and full visibility into every routing decision.
You can jam on the Albatross Github, or if you brew, just type the following:
brew update && brew upgrade albatross
Saturday nights are for shipping. Just shipped Albatross v2.1.0 🎉
Transparent model routing has always been at the heart of Albatross. You should be able to understand exactly which model did what, what effort level it used, how many tokens it consumed, and what it cost.
This release takes that transparency even further.
Before a task runs, Albatross now shows every configured candidate model, its selector score, confidence, estimated cost, and a bunch of other interesting stuff.
If routing policy changes the selector’s choice, you can see the exact fallback and why it happened.
You can now set explicit routing policies around quality, cost, minimum confidence, local-only operation, effort support, per-turn spending limits, and models with unknown pricing.
After the work runs, Albatross records the actual provider and model used, requested versus effective effort, token usage, latency, cost, and outcome in a durable local receipt.
Also some snazzy new slash commands:
🪽 /route simulate previews a route without changing models
🪽 /route why-not explains why another model was not selected
🪽 /route report summarizes routing decisions, confidence, outcomes, models, and spend
🪽 /route label records whether a route succeeded or failed
This is the part of Albatross I’m most excited to keep building: multi-model routing that is powerful, configurable, and completely inspectable.
Upgrade:
brew update && brew upgrade albatross
albatross.sh
Two different ideas for the Albatross website, which do you like more? Let's call the first 1, the second 2.
Kinda logical right 😅
And of course, you can also share if you don't like either!
Two different ideas for the Albatross website, which do you like more? Let's call the first 1, the second 2.
Kinda logical right 😅
And of course, you can also share if you don't like either!
Okay, announcing the new name for Small Harness.
Very excited about this, may take a week or two to do all the repo changes, domain updates, etc.
But soon, Small Harness will become Albatross.
Same mission. A free open source harness where local and frontier models play nicely together.
As local AI continues to progress, I think we're going to see this combo as a powerful one, and I hope Albatross can help devs leverage both in a fast, easy, and fully transparent way.
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