dsh-anchored-standard

DeepSeek Harness (dsh) is an open-source agent harness developed by DeepSeek AI. It uses an architecture in which everything is a plugin and is powered by Cordis, whose design is described in “A Programming Paradigm for Spatiotemporal Composability.” The npm package can launch a local Web UI with `npx @deepseek-ai/dsh web`, serving at `http://127.0.0.1:3080` by default and opening the default browser; it can also be built and run from a repository checkout. The project is in developer preview and warns that compatibility-breaking changes may occur. It is licensed under the MIT License, with third-party dependencies and their licenses documented separately.

DeepSeek and Destroy (DSD) is a long-horizon coding-agent skill for executing large implementation plans through persistent worker loops. A premium parent agent handles architecture, decomposition, decisions, and phase gates, while fresh lower-cost specialist workers implement, review, repair, and recheck repository-scale changes. The default worker backend is external OpenCode using opencode-go/deepseek-v4-flash, and the skill is designed for Codex, Claude Code, OpenCode, Kilo Code, and comparable coding harnesses. Each task is rendered into an immutable JSON contract and managed through attempt directories containing prompts, reports, logs, state, and scope baselines. Its normal loop uses an Implementer, a fresh independent Reviewer, and—when needed—a fresh Fixer followed by another Reviewer. Python-based gates check objective integrity such as hashes, lifecycle, and exact source movement; an optional read-only Evidence Clerk interprets already-produced evidence for the parent but cannot invent proof, rerun verification, repair code, waive integrity failures, approve work, or recurse into another Clerk. Documentation is split between always-relevant parent rules and cold-loaded workspace, harness, transport, compaction, prompt, and specialist-role materials.

DeepSeek (深度求索) is an AI research project and model provider that develops and open-sources large foundation models (notably named DeepSeek-V4 and DeepSeek-R1) and provides hosted inference via a chat interface (“DeepSeek AI”) and an API. It publishes open-source model releases and offers a hosted API for text-based prompt inference; video reports state DeepSeek models can be exposed as external backends and routed into the Codex model picker via Codex Router.

DwarfStar is a self-contained, model-specific native inference engine for running DeepSeek V4 Flash, GLM 5.2, and, on high-memory systems, DeepSeek V4 PRO locally. It combines model loading, prompt rendering, tool calls, persistent KV state, an HTTP server, and a coding agent rather than serving as a general GGUF runner. The engine supports Metal on Macs, CUDA including multi-GPU systems, and ROCm on Strix Halo hardware; it also provides SSD streaming for machines with insufficient RAM, distributed tensor and pipeline parallelism, and server-side micro-batching for multi-user inference. The repository includes tooling and data for GGUF, imatrix, quality, and speed testing, and acknowledges code and design contributions from llama.cpp and GGML.

deepsec is an open-source, agent-powered vulnerability scanner and security harness from Vercel Labs for on-demand review of large codebases within the user's own infrastructure. It identifies candidate vulnerabilities, uses AI models to investigate them, supports triage and optional revalidation to reduce false positives, and can run work across parallel worker machines. The CLI initializes a repository with `npx deepsec init`, stores state and findings in a `.deepsec/` directory, and resumes interrupted runs while skipping files already analyzed. Subsequent commands separate fast pattern scanning from AI processing and revalidation, and findings can be exported as Markdown directories or JSON. Model access can use Vercel AI Gateway, direct OpenAI or Anthropic credentials, or a custom HTTPS provider; scan cost and duration can be capped with command-line options.