Agent frameworks, multi-agent orchestration, tool-calling and workflow engines.
Git worktree plumbing for running several coding agents at once without them wrecking each other's working tree.
A curated set of reusable skills for coding agents — the difference between an agent that finishes tasks and one that finishes them your way.
The terminal-native agent that made agentic coding mainstream — and the reference point every other coding agent is measured against.
Runs many coding agents in parallel while still using the subscriptions you already pay for — the cost model is the product.
Strips the tell-tale rhythm of model output from generated text — useful, and a reminder that the tells are now well known.
An explicit, readable list of the twenty-odd patterns that make text read as generated — better as a checklist than as a filter.
Gives an agent continuity across sessions — the missing piece once users expect it to remember them.
The format question for agent capabilities is being settled here, and it is just a folder.
Web access for agents without paying per-call — including the platforms with no usable API.
Treats the context window as a budget with a line item, not a bucket you keep pouring into.
Puts the specification back in front of the code, which is the only way agent output stays reviewable.
Not a tool but a method: encode how your team works, then let the agent follow it.
Vendor-published plugins for the jobs knowledge workers actually do — a usable starting template.
Model agents as explicit state graphs — the difference between a demo loop and a controllable system.
Self-hostable LLMOps platform with visual workflows, RAG and prompt management in one box.
Role-based multi-agent orchestration — readable when you have to explain it to a manager.
Conversation-driven multi-agent framework with strong code-execution tooling.
The largest integration surface in LLM tooling — most useful when you need a connector today.
For two years the advice was to write better prompts. That advice stopped paying off somewhere around the point where the model became reliably good at following instructions. Wha…