World Wire

In this tutorial, we build an advanced workflow around Anthropic’s financial-services repository and reproduce its skill-driven architecture in pure Python. We begin by installing the required libraries, cloning the repository, and programmatically mapping its agents, vertical plugins, partner integrations, managed-agent cookbooks, and financial analysis skills. We then parse the repository’s SKILL.md files into a searchable registry and construct a reusable SkillAgent that injects selected financial playbooks into the Anthropic Messages API while supporting an iterative tool-use loop for Python calculations and file generation. Using this architecture, we execute a synthetic discounted cash flow valuation, generate a WACC and terminal-growth sensitivity heatmap, perform comparable-company analysis with formatted Excel output, draft a private-equity investment committee memo, and inspect a managed-agent deployment specification without sending a live deployment request. Copy Cod...

Perplexity has released pplx , an official command line client for its Search API. The tool returns grounded search results and extracted page text, all as JSON. According to its docs, it targets humans and coding agents equally. It is not a chat client. There is no conversational mode, no model selection and no synthesized answer. Two surfaces, one output contract The tool exposes exactly two working surfaces. pplx search web runs a live web search. pplx content fetch pulls a URL and returns cleaned page text. The contract around them is the interesting part. Per the official pplx-cli Agent Skill , success means exit code 0 and exactly one JSON object on stdout. Search returns {hits: [{url, title, domain, snippet, ...}], total, saved_to?} . Every failure exits 1 with an empty stdout. One JSON error object goes to stderr, shaped {"error":{"code","message","command","hint"?}} . Documented codes include AUTHENTICATION...

The KwaiKAT Team at Kuaishou has introduced the KAT-Coder-V2.5 . It is a coding model trained to operate inside real, executable repositories rather than emit single-turn code. The served model is available through StreamLake . An open-weight variant, KAT-Coder-V2.5-Dev , was released separately on Hugging Face under Apache-2.0. AutoBuilder: environments that actually run the intended tests The research frames a verifiable task as a triplet. It needs a precise task description, an executable repository environment, and a set of validation tests. A patch is correct only if it passes all of them. Tasks are mined from real pull requests and commits, following the SWE-bench lineage. The merged code change supplies a golden patch and the accompanying test change supplies a test patch. Raw issue text is discarded as a specification. Instead, descriptions are regenerated into three parts: a problem statement grounded in the golden patch, requirements derived from the test patch,...