Plugins

Study coach for DeepSeek Harness: turns a course into a knowledge map of subject, module and unit, records mastery per unit in six stages, plans daily tasks against a materials index, keeps a wrong-answer book and spaced-repetition cards, and serves its own web panel.

Session progress tracking for DeepSeek Harness, without digging through the logs: the agent keeps a live nested checklist of the work — from a whole phase down to a single step — and every item carries a weight, so the ring and the % pill in the composer dock row always match reality. Hover it for the current activity, or open the Session Progress tab in the native right sidebar for the goal, the weighted checklist with per-item shares, the next steps and the working notes; when the session ends, the same checklist stands as a clean record of what got done.

Records real clicks, inputs, navigation and network traffic in a user-guided browser session for DSH, then generates a Markdown timeline report (report.md + events.jsonl) to build API-level skills.

Reading archive for dsh: after reading open-source code, capture quick notes or write full deep notes that group into one card per repo / file / symbol, stored as an append-only log of Markdown notes you can open in Obsidian; query your history, browse recent reads, or search your own Obsidian vault and link related notes to a reading record. Nine tools, a /codevault command, and a code-reading skill.

Full-featured record & replay for DSH (works on Windows) from the huahua plugin series: replay every auto-recorded session as a readable timeline, export/import shareable replay packs, re-run conversations in a fresh session, and record screen operations to auto-generate installable SKILL.md skills. Includes a 4-file Windows adaptation of kangshifu1/dsh-record-replay for DSH rc.5 (see README derivative notice).

SSH terminal panel and AI connection manager for DeepSeek Harness: model-driven SSH connections (connect/exec/list/status/disconnect), auto-saved connection records, keep-alive + auto-reconnect, execution mutex, credential-safe auth, and an XShell-style m

Shows DeepSeek balance and estimated daily spend, merges external vision-call JSONL records, and adds a per-session dashboard with model statistics, TTFT, cache rate, call logs, cost estimates, filters, and CSV export.

Delete one finished turn from a DSH conversation without deleting the session — the trash button next to the last assistant reply removes the question, that reply and the tool records of the turn from the conversation surface and from the model context, while the session id, title, later turns and the append-only log stay; the removal is written as a persistent tombstone, so it survives a reload.

On-demand skill tools for DeepSeek Harness: registers skill_search / skill_load / skill_ref so the model searches a staged skill library first and loads a skill body only when it needs it, keeping the library out of the resident session catalog and out of every turn's context; adds a Skills tab to the conversation view ring that reads back the whole session and lists which skills were actually loaded, and in which turn. Zero dependencies, and the records render client-side only, never entering the model's context.

Personal paste inbox for DeepSeek Harness (dsh): /inbox in the composer or the sidebar panel files links, images, text and credentials into a local vault, classifies them by local rules and then by a rate-capped model pass, and browses, searches and edits them from the panel; the assistant retrieves records on request in conversation, credential bodies stay encrypted at rest, and an optional WebDAV or S3 remote syncs records and attachment bytes. Windows only so far.

Simulated life context for DeepSeek Harness: every turn injects the past 24h of simulated life events from the workspace .life/ directory (sliding-window filter, session-level deduplication with delta updates, world summary) as a collapsed context notice, and the life_react tool lets the agent record feelings, thoughts and actions back into its life log for the next round of world evolution — turning a DSH agent into a roleplay character with a persistent daily life.

A local-first personal state record and decision engine for dsh: keeps every input byte-for-byte with line-level provenance, argues against its own conclusions by generating defeaters first, ages each stored fact with its own TTL, and reports where a decision rests on nothing at all.

Per-project memory for DeepSeek Harness. Three Markdown files per workspace — PROJECT.md, DECISIONS.md and SESSIONS.md — are auto-created on the first step of any session in that workspace, re-read from disk and re-injected only when they change (and re-injected if compaction dropped them), and written back by classification through a memory_checkpoint tool, with a bounded end-of-turn nudge when a turn did work but recorded nothing. memory_read and memory_search read the live log and the archive, the latter over a zero-dependency BM25 index. The session log is capped at 200 entries with the overflow moved to SESSIONS-archive.md — never injected, but visible, readable and searchable, and restorable one entry at a time. Settings page: a workspace list with a path filter, read-only tabs for the three memory files plus the archive, reload, export/import of one workspace's memory as a JSON bundle, a two-step clear, a panel that rewrites or removes the AGENTS.md instruction block, and a PROJECT.md staleness reminder. A composer status chip shows that workspace's sync state and creates the files on click. Zero dependencies — no vector store, no embeddings, and no model calls.

Feishu (Lark) integration for DeepSeek Harness: 25 tools for chat messages and history, cloud documents (including knowledge-base pages, generated charts and images), bitable records, spreadsheet ranges and drive permissions, using your own enterprise self-built Feishu app.

Context manager for DeepSeek Harness: auto-summarizes every turn into priority-sorted records, injects them plus pinned cross-session notes and custom text into each model request, and folds any-size real conversation ranges into summaries to save tokens. Persistent and restart-safe. NOTE: manual multi-step install — copy the three package folders into profiles/node_modules and add the provided cordis.patch.yml rows, then restart DSH; not a standard one-command install.

Read-only Odoo tools over JSON-RPC: server info, model field introspection, and a restricted search_read limited to an allow list of models whose domain field names may not contain dots, so related-record traversal is not possible. A draft-create tool is registered only when allowWrite is enabled, and is limited to sale.order and project.task with the draft state enforced by the plugin.

Electrical and electronics calculation plugin for DeepSeek Harness: every computation runs through dedicated tools on self-describing complex value objects in SI base units, with an isolated calculation agent preset and a records panel that archives every solve on disk.

Decision-and-goal memory with lineage: explicit commands and a model tool record decisions deterministically, a status card re-anchors them across compaction, a lossless event stream with BM25+jieba retrieval backs it, and a scenario-level fidelity regression suite gates releases.

Keeps a local task-outcome ledger for DSH, verifies acceptance criteria from deterministic evidence, records user disposition and token usage, and supports digest-bound export.

Self-learning loop for dsh: record lessons, draft and promote skills, periodic curator review that corrects, consolidates, and retires skills.

Smart form skill: structured record-keeping for bills, ledgers and logs with auto-categorization and periodic reports.

Let a local DeepSeek Harness Agent use BailingHub to query data, update records, and run permitted actions in an online store, SaaS, or other admin system.

Evidence-first guard: warns the agent when it claims success without a matching tool-execution record in recent context.

Self-maintaining handoff memory per working directory and git branch: records turns, folds them into concise Markdown, and injects the result into future sessions from ~/.agent/agent-handoff, byte-compatible with pi-handoff.