Plugins

The memory that dreams — cross-session memory for DeepSeek Harness: recalls you and your projects across sessions, consolidates memories while idle (autoDream), freezes conflicting memories for your review, and keeps a replayable audit trail. Memory stays on your machine as SQLite with human-editable Markdown mirrors; four-way recall (keyword, vector, BM25, entity graph) and an interactive memory panel ship with it, plus 10 model tools, an MCP server, an external API and a CLI. Summarization and consolidation run on the host model you already configured; with a local embedder, semantic search runs fully offline.

Deep reading & summarization for DSH: books/papers/videos/web into structured Obsidian notes via plugin parsers, MapReduce parallel deep-read subagents, JSON Schema outputs and an idempotent cache.

Token-cost pipeline for DeepSeek Harness: pressure-aware layered compaction (lossless projection below 40% context pressure, LLM summarization above), per-agent tool allowlisting, long-text-to-image with vision summarization, and a /token-status command tracking pressure, tiers, and saved tokens.

Media and vision workspace for DeepSeek Harness: image, video and speech generation, image Q&A and element locating, long-image OCR, pixel diff, HTML-screenshot verification and video summarization, with DashScope and OpenAI-compatible providers, model pools and a workbench client.

Cross-session memory plugin for DSH (v0.6.1, npm @asherliner/dsh-memory-connect): auto-extraction, SQLite FTS5 indexing, RRF semantic recall injected into the system prompt every turn, scheduled maintenance, LLM-powered consolidation via ctx.llm, context explosion prevention, and global Soul identity via ~/.dsh/soul.md. v0.5.0 added temporal context graph (valid_from/valid_until/supersedes, append-only corrections via reviseMemory), trust model (recalled history injected as untrusted reference, current instruction always wins), turn-end summarization. v0.6.0 added local semantic embeddings (BAAI/bge-small-zh-v1.5 via embed_server.py, cosine + RRF fusion with FTS5, no cloud calls, ~232 msgs/sec on CPU). v0.6.1 fixed ~ expansion in path config. Zero-config install.

Codex-style context window auto-management for DeepSeek Harness: a lossless rollover engine with zero summarization model calls, task-oriented handoff anchors, working notes that survive compaction, verbatim recall of archived windows, and a stale-notes gate that downgrades to an explicit warning instead of vouching for outdated notes. One-click composer button plus /smart-compact command, three-band automatic rollover, mandatory anchor sanitization; works out of the box with zero configuration.

Model-driven context-window rollover bundle for the DeepSeek Harness: fresh working context, durable model-managed notes, a small verbatim recent tail, and targeted history recovery — no summarization.

Long-task orchestration loop: Codex plans/scores/reviews, DeepSeek executes, Kimi supplements (vision acceptance, summarization, cross-check).

Personal dsh preferences: a tunable companion to the official compaction engine (threshold, retention, summarization model/reasoning, turn-end compaction), llama.cpp model import for the Models page, and tab/notification helpers (status-light favicon, bro

Context trimmer: lists the current session's context entries with role, preview and ≈token estimate (cl100k), highlights over-threshold items, and removes selected entries exactly without LLM summarization.

Data analysis toolkit: CSV/TSV/JSON profiling, IQR and z-score anomaly detection, structured summarization with quality issues, and code-free filter/group/aggregate queries.

Context compression skill for DeepSeek Harness -- intelligent conversation summarization

Kill AI Slop for DSH — score a received document on three weighted axes (expression, execution, decision), audit work-slop with a delivery-obligation ledger, and machine-verify every quote against the source. Reads docx, pptx, xlsx, pdf, txt, md, csv, json and html. Zero runtime dependencies, zero network, fully local.

Semantic context watcher for DSH agents: maintains a journey ledger with flash summarization and MinHash novelty detection, folds milestones, and can inject long-term context with a three-level stall response; injection and the stall-2/3 responses are off by default.

Stops compaction summaries and session titles from burning their output budget on reasoning, by lowering the thinking level and raising the token floor for auxiliary calls only.

Archive DeepSeek Harness sessions into a self-hosted WeKnora knowledge base with extraction, summarization and incremental dedup.

Rapid-refill circuit breaker for DeepSeek Harness automatic compaction. It refuses a compaction that would be futile — the context refilled within fewer than N tool turns M times in a row, which the unbounded step-pressure trigger cannot detect — and instead of burning a summarization call on every step it reports the situation with advice, usually that a single read or tool output was too large. Shows state and re-arms through /compaction-breaker, and injects one prompt section so the model relays it to the user. Covers host-plane sessions through its profile bundle; ordinary sessions need one row replaced inside an agent preset.

CWL — Context Window Lifecycle for DeepSeek Harness: structured context eviction (arXiv:2606.11213). Graduated, deterministic, zero-LLM eviction of exploration/action episodes when context pressure exceeds budget — no summarization lossiness, no hallucina

One-click context compression for the dsh web GUI: a 压缩 button on the session title bar summarizes the whole conversation into a few lines, opens a new session in the same workspace seeded with the summary, and switches to it — the original session stays untouched.

Compaction backend replacing LLM summarization with a deterministic semantic extractor (keeps code/paths/commands, drops chatter) plus 28.4x KV-compression accounting.