The "context-management" topic on GitHub groups 29 open-source projects in the DeepSeek Harness (DSH) ecosystem, led by Tianshu-harness with 960 GitHub stars. Tianshu-harness — Tianshu is a terminal coding agent runtime built on the harness project (Tui X Gui), with prefix-cache engineering optimization for DeepSeek V4 (measured steady-state hit rate of 97–99% in long sessions) and deep adaptation. Every project here is indexed by DSH Universe with live GitHub data — stars, activity and install status — so you can compare and install directly.
Tianshu is a terminal coding agent runtime built on the harness project (Tui X Gui), with prefix-cache engineering optimization for DeepSeek V4 (measured steady-state hit rate of 97–99% in long sessions) and deep adaptation. It breaks out of the traditional AI coding assistant's limit of treating the LLM merely as a tool, and is built on a cognitive virtual machine (CVM), a self-awareness layer and Stigmergy self-decaying memory, making the AI a development partner with independent judgment and cognitive safeguards.
Model-driven context management (Active Context Pruning / ACP) for the DeepSeek Harness — the model decides when and what to compress. Ported from billion-context-pi (ranxianglei); acp-kernel reused verbatim. CompactionEngine backend with compress/decompress/search_context/acp_status tools.
DeepSeek Harness plugin: see what your agent can actually reach — skills, MCP servers, system tools with true in-context state, and per-session / per-preset switches
Context housekeeper for DeepSeek Harness: remembers “what you're doing right now” for you, automatically curating the context sent to the model — keep what should be kept, delete what should be deleted, leave uncertain items untouched, so long AI coding sessions stay on track and every token counts.
Verdict-based context compaction for DeepSeek Harness — replaces lossy LLM summaries with fast keep/truncate/drop decisions from jev-latest; everything kept stays verbatim. Port of tamaratran/fast-jev-compaction.
Persistent, searchable, per-project memory for the DeepSeek Harness: decisions, rules, and session context in a queryable DuckDB file, with the rule set injected into every model request — plus a full management UI in the Web Client.
MOVED to @yadsh/dsh-sleev in xarleyn/dsh-plugins — Sleev integration for DeepSeek Harness with route-aware LLM telemetry and context-optimization observability