Plugins

Red-team engagement mode: send one target organization name and a planner session runs a five-role execution team (recon, asset triage, vulnerability discovery, exploitation, internal pivot) at up to three concurrent agents, preflight-checking skills and resources and asking once for any missing key or VPS first, guided by a built-in first-run onboarding skill; scoring follows the merged intrusion scoring rules (8 categories / 25 points) with server-side caps, highest-privilege-wins and per-service dedup, and self-registered accounts never score; findings land in a local SQLite fact base with discovery timestamps, shown in a persistent right-side console of 12 tabs (asset mapping with a discovery timeline, agent roster, session/tunnel state, five-stage attack chain, scoring targets, a report that spells out how each score was obtained — actions, exact commands, credential provenance, tunnel build commands — a category-organised POC/EXP knowledge base and a skill library with per-skill usability verdicts); ships 23 native skills, 53 redteam_* tools and one-command self-update.

Claude Science-style research workbench: ReAct research-loop engine (research_* tools), versioned artifacts with provenance (artifact_* tools), and 10 science skills for genomics/pathogens/bioinformatics.

Research-only trading workbench bundle: typed market-data provider seam with a CSV reference provider, multi-timeframe indicator regime snapshot and OHLCV tools, interactive chart cards in dsh web with provenance-gated model annotations, and a risk-guard denying execution-shaped tool calls at tools/pre-execute.

Local-only project memory with zero bundled runtime dependencies or external services: JSON as the source of truth plus generated PROJECT_MEMORY.md, token-bounded session-frozen Hot Memory for prompt-prefix cache stability, cached cross-project BM25 recall, trusted session/turn provenance, explainable pre-write duplicate/conflict governance, editable importance/pin/tags/supersede/archive lifecycle, configurable top-level turn-end distillation, and a bilingual Web GUI for search, inspection, diagnostics, and live settings.

Local literature knowledge-base RAG for DSH: hybrid BM25 + vector retrieval, cross-encoder reranking, cited answers with section- and page-level provenance, metadata-only refresh and background ingest with progress polling, over a SQLite index.

Reproducible science workbench: agent-driven cells, inline figures with feedback/rerun, manifest provenance, environment snapshots, and publication-grade figure skills (9 bio_* tools + workbench UI).

Live security beacon for DSH that follows tool activity. Click to view call statistics, risk provenance chains and blocked actions, with read-only task restrictions and tool metadata change detection.

Evidence-backed inspector for DSH Web built-in capabilities: runtime/config provenance, compatibility and drift diagnostics, plus fail-closed controls for nine reviewed UI leaves.

Technical-preview local graph memory for DSH and Codex: recalls owner-global and current-project evidence before each turn, writes USER and ASSISTANT records separately, and preserves project, session, actor, and source provenance for a visual atlas and cited knowledge pages.

Technical-preview local graph memory for DSH and Codex: recalls owner-global and current-project evidence before each turn, writes USER and ASSISTANT records separately, and preserves project, session, actor, and source provenance for a visual atlas and cited knowledge pages.

Math Agent Framework for DeepSeek Harness: symbolic derivation engine (CES / quadratic forms / ODE / PDE), SymPy verification, Lean 4 compiler-verified formal proofs, and QED-style multi-agent adversarial verification, exposed as native DSH tools through a TS shell bridging a Python engine. Requires cloning the math-agent-framework repo and `pip install -r requirements.txt`, with MATH_AGENT_HOME pointing at the repo root. Every result carries provenance (engine versions, seed, tolerances) and is marked untrusted data.

Read-only insight panel for one profile: five views over the same data — config layers, plugin tree, services, tool names and models — each entry showing which layer inserted or disabled it and whether it is running.

Content-addressed artifact, fact, action and report lineage for DeepSeek Harness

Business knowledge-network context for DeepSeek Harness: bind a session to an OpenBKN knowledge network, query its objects and metrics through managed MCP tools, and open trace-backed provenance (execution facts and a business graph) for each answer. Ships with the OpenBKN Runtime; the provenance views need an OpenBKN enterprise license.

Human-governed cross-session memory spaces with independent source and consumer relationships, provenance, versioning, and pre-send injection review.

Hand off focused context without waiting for or interrupting the active Agent: freeze a bounded Session snapshot, summarize it asynchronously with an isolated no-tool LLM, and deliver a provenance-bearing capsule to another Session or an authorized Room—quiet by default for Sessions, with explicit wakeup available.

Long-term memory for DeepSeek Harness in Claude Code's format: private, overlay, or shared with Claude Code, with provenance on every file

Summarises the case evidence, diagnosis, repair procedure, parts list and cost-option comparison for a motor into a Markdown repair recommendation report with data provenance.

DeepSeek Harness (Cordis) plugin — bi-temporal VSA memory + cognition engine + BLAKE3 provenance, exposed as a DSH storage+session plugin. End-to-end tested with a real Python subprocess.

Pre-install supply-chain checks for DeepSeek Harness plugins: verify the tarball you are about to install matches the source you read, before any code runs.

Provenance-aware execution security for DeepSeek Harness. Track sensitive data across tool calls and stop risky side effects before execution.

Trusted office suite for government/enterprise work by Beijing Caizhi Technology (深知可信智能): three skills — trusted consulting (policy/regulation Q&A with citation markers + provenance HTML), trusted search (authoritative policy/standard retrieval with traceable HTML + clean Markdown), and official-document writing (draft/rewrite/Word/red-head delivery); all interfaces go through the dknowc trusted workbench MCP (Bearer auth), products land in the session workspace, one-time key setup persists for later sessions; ships on npm as dknowc-dsh.

Skill that fact-checks a claim against the open web rather than model memory: it splits the claim into independently checkable fact points, routes each point to the primary-source ladder for its domain (policy, academic, medical, financial, disaster and accidents, food safety, science, education, sports, entertainment, judicial, and more), searches domestic and international ecosystems in parallel, fetches primary pages, grades sources by type, re-searches with debunking keywords, and reports conclusion-first with a full URL and citation position behind every statement, keeping unverified and undecidable points separate from confirmed ones. Three factual judgements can be routed to a TypeSafe Jev (System One) decision model when a key is configured, falling back to the skill's deterministic rules when it is not; a model verdict can only lower a confidence tier.

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.