400 results
Cross-session memory cue bank for DeepSeek Harness: builds a persistent event-cue library (keywords, user language idiosyncrasies) and re-activates remembered event details on topic switches, mirroring human episodic recall.
Model-authored context pruning for DeepSeek Harness through the official compaction API.
DeepSeek Harness plugin (temporary, pre-upstream-fix): automatically injects a CPython tempfile shim (PYTHONPATH -> sitecustomize) into every confined shell command on the Windows sandbox, so python/pytest tempfile use works with zero extra tools, zero model-context overhead, and zero escalation.
Expose DeepSeek Harness agent capabilities as an MCP server, so an external MCP client (e.g. Hermes) can drive Harness to execute coding tasks. Hermes = brain, Harness = arms.
Inspect and manage the skills, tools, and MCP capabilities available to a DeepSeek Harness agent session.
dsh-plugin: OMP-style ingress shaping plus optional local /fast-compact. Can replace DSH /compact and auto-compaction with a mechanical fold.
Configurable Codex-style conversation navigator for the DeepSeek Harness Web GUI, with compact previews and fast paragraph jumps.
Per-workspace MCP scoping for the DeepSeek Harness — decide which MCP servers a session may see from the directory it was opened in.
DeepSeek Harness 上下文自动压缩、手动压缩与溢出恢复插件
DeepSeek Harness (dsh) profile bundle that registers the MathWorks MATLAB/Simulink MCP server into the GUI so agent sessions get mcp__matlab__* tools.
DeepSeek Harness bundle for a Windows desktop UI context picker and MCP server for Codex, DeepSeek Harness, and AI agents
Lifecycle orchestration engine for AI agent teams on DeepSeek Harness with task-scoped Git worktrees, state-gated delivery transitions, and off-context memory.
DeepSeek Harness bundle for AI NetCafé's hosted tools. One install for the full catalogue, or pick one of four focused packs (tables, dev kit, doc flow, China facts) so you only pay the context cost of what you use.
Native knowledge context for DeepSeek Harness
上下文工程：按层级（规则文件→规格→源码→错误输出→对话历史）主动策划 agent 看到的信息，提升输出质量。受 addyosmani/agent-skills（88k★ MIT）启发。
Context compression skill for DeepSeek Harness -- intelligent conversation summarization
dsh-docker — typed, guarded container control for DSH: structured docker/compose tools, project-aware targeting, an approval gate for destructive ops, service-health context, and a replayable status-table renderer
Markdown folder long-term memory for DeepSeek Harness: one file per fact, an index line per memory, mounted into every request as a system prompt section
Claude Code-style `paths:` rule injection for DeepSeek Harness (DSH): inject rules from ~/.dsh/rules, <project>/.dsh/rules and <project>/.claude/rules into the model context.
Forgetting engine for AI agents — memory TTL, decay, eviction, audit. The opposite of memory programming.
元压缩：模型自己决定何时、如何压缩自己的上下文——列 surface、选区间、以自写文本替换；替换走官方 compaction 事务（检查点、配对平衡、可重建）。Meta-compaction: the model directs its own context compaction through the official compaction seam.
Pure-incremental directive-driven compaction for DeepSeek Harness: /compact-directive <requirement> summarizes the session middle per your requirement, /trim-directive <requirement> trims the whole conversation per your requirement
MCP adapter for DeepSeek Harness — one proxy tool instead of dumping every MCP schema into context.
把 git 状态与仓库规范动态注入 system prompt：分支/脏文件数/最近提交 + 仓库规范指引（官方 system-prompt section/context/variable 缝隙插件）