Plugins

Polaris Memory: local-first project memory plugin for DeepSeek Harness. Uses per-project .dsh-memory.json; provides memory_read/recall/write/update/delete tools, /memory command and settings UI, with tiered injection (resident user profile + scene-triggered memories with P1/P2/P3 importance), semantic recall (IDF + synonym layer), and a hard-guard mechanism for bottom-line memories (detect deny-semantics -> authorize -> block AI deletion; user can confirm-override).

本地优先的 Harness 运行遥测插件：记录请求、模型、工具与插件生命周期指标（延迟、Token、成本、错误、缓存），默认不采集内容。Local-first Harness telemetry plugin for DeepSeek Harness. npm 包 dsh-local-telemetry（dsh-telemetry 名已被第三方占用）。

Approval-gated workspace instructions and memory for DeepSeek Harness

dsh-plugin: quality-first topic memory for dsh — a topic keeps the starting question, conclusion, impact and dependencies, not the process; local-first git-traced OKF bundle, budgeted LLM-free injection

Local-first control plane for managing multiple DSH runtimes, profiles, presets, sessions, plans, and knowledge references.

Local-first personal usage insights in Settings, with 1/7/30-day token heatmaps and a 30-day calendar, token composition, model mix, and skill-call status.

Local-first DeepSeek Harness plugin marketplace with GitHub and dshfind providers

Local-first token usage heatmap inside DSH settings: GitHub-style week/month/quarter/year grids, hourly usage per day, per-model and per-provider Top 5, and persisted history that survives session deletion. Zero network, zero billing.

Local-first usage and cost meter for the DSH web UI: composer button with live session cost and balance; panel with a stacked per-model daily/7-day chart priced per effective list-price interval (official pricing page synced daily), monthly usage tiers with a canvas share card, 30/50/85% context-pressure warnings with one-click /compact, budget alerts, and an in-panel npm update check with one-click update.

Local-first Agent Experience Network for DeepSeek Harness, distilling task-level experiences from traces and live manifests, grading by H0-H4 evidence, discovering by compatibility, and promoting only after explicit review.

Local-first code knowledge graph for coding agents: 10 MCP tools for layered context compression, DAG planning, incremental AST indexing, a cross-session skill flywheel, diagnostics, and graph artifact import/export.

DeepSeek Harness (DSH) plugin for local-first automatic Wiki memory and native Skill generation.

Install iHow Memory as a local-first shared memory plugin for DeepSeek Harness.

Local-first persistent memory for DeepSeek Harness: bounded pre-step hot-memory injection, exact and Chinese-bigram BM25 cold recall, six agent tools, approval-gated lease-lock writes with recovery receipts, and read-only governance and trajectory-review candidates.

Local JSONL run traces for DeepSeek Harness sessions

Privacy-first Markdown and self-contained HTML sharing for DeepSeek Harness sessions

Password + CIDR gate for DeepSeek Harness web / DeepSeek Harness 局域网密码门禁

DeepSeek Harness community Bundle for local, evidence-backed Agent Memory

Workflow tools for the local aflare binary: generate, validate and run local-first deterministic YAML workflow DAGs (WAL crash recovery, Saga compensation) through the local aflare binary, with 300+ templates built in.

PLUR memory rendered into the system prompt on each assembly rather than exposed as a tool call, so the block is replaced instead of appended and context stays flat across a session. Fully local hybrid search (BM25 + BGE fused with RRF), plain YAML storage you can edit, per-workspace scoping, and a /plur-memory browser.

Export complete Web Sessions to local Markdown or self-contained HTML, with stable rendered previews, default redaction, and opt-in bounded tool-call details.

Local-first four-bucket Token observability: persistent session/provider/model/day dashboards, trends, budget and anomaly signals, public-rate estimates, safe aggregate exports, and explicit opt-in usage or session-trajectory analysis.

Local-first learning mode: cross-session learning threads with per-source explanations.