Plugins

B2B lead generation skill: search target companies by industry/product/region, cross-validate and extract contacts.

Registers a SpecWorkflow skill pack for requirement clarification, implementation specs, execution, delivery review, repair planning, bug diagnosis, and source-backed research.

TuneTune for DeepSeek Harness: train, test, and improve small models with your Agent, with a workbench beside the conversation.

Apache-2.0 port of the caveman skill family (JuliusBrussee/caveman) into DeepSeek Harness as 14 native skills — three terseness levels (caveman, ultracave, megacave) plus commit, review, help, stats, an in-session compress whose gate rejects a dropped code block, heading, URL, negation or env var, or a result that did not shrink, and six workflow-discipline skills; commands, paths and error text stay verbatim.

Five skills for a reviewable engineering incident journal: record an event only when a counterfactual can be written, quiz yourself from the existing entries, audit the journal for decay, ingest outside material together with its provenance, and rename a layout directory while rewriting every reference to it.

Apify Actors for DeepSeek Harness: adds the Apify MCP server to your profile.

Multilingual writing, chunked long-form collaboration and continuity review, with on-demand DSH delegation discovery. Requires Python 3.9+ on PATH.

Browse, preview and install public Agent Skills from inside the DSH web GUI, aggregating five sources (claudeskills.info, skillsmp.com, the awesome-claude-skills repository list, the official anthropics/skills repo, and skill packs shipped by installed DSH plugins). Skills install pinned to a commit rather than a branch name, so what you previewed is what lands; the panel reports provenance, whole-tree update checks and a trash instead of deleting. Before writing anything it validates the skill name and frontmatter against the rules the harness silently enforces, lists files that SKILL.md references but the fetch did not bring, flags partial fetches, and offers overwrite, rename or skip when a name is taken.

DSH hardware sandbox plugin: assemble a 3D scene of ESP32 / BME280 / PIR / LED components with protocol- and voltage-checked port wiring, run real Python project code in the loop against simulated I2C/GPIO hardware with fault injection, let networked device simulators report over HTTP to a real backend (validated end-to-end against a live seat-reservation system), observe a real device read-only and map its state onto the scene, and add support for new boards through data-driven pin definitions. Ships 16 hw_* agent tools plus a bundled SKILL.md.

Read-only audit of the local CLI toolchain as a sidebar panel in the DSH web GUI: lists installed versions across Homebrew, npm global, pip, Rust/Bun/uv and self-updating CLIs, flags which ones have a newer release available, and shows the dependency impact for installed packages. It reports only and never runs an upgrade, so no tool on the machine is modified. The DSH plugin ships on npm as `dsh-cli-doctor`.

Trip-planning agent preset for mainland China that answers in Chinese: queries 12306 train availability, Fliggy and Tuniu flight and hotel prices, and real Amap transit routes, checks closures and weather, and delivers a single offline HTML roadbook with draggable maps, three hotel price tiers and an itemized budget. Ships 9 skills, an environment doctor that walks users through missing API keys, and a patch for the 12306 MCP server; it plans and queries but never books or pays.

SQLX database tools: list saved datasources, show or test a connection, execute SQL and open a local result page, with the sqlx CLI installed on first use.

Three-tier agent memory harness: L1 always-on CLAUDE.md, L2 index, L3 detail skeleton with templates, a gate that blocks writes to protected files without a one-time approval token, zero-judgement event logging, weekly distillation, and a TDD execution-loop skill.

AIEO (GEO/AEO) delivery method as one isolated skill provider: AI-visibility diagnosis on a 0-9 score, positioning, search-term mining restricted to whitelisted platform exports, periodic monitoring and an HTML monitoring dashboard, chained by one shared question library, plus a landing-page cloner.

Superpowers (obra/superpowers) for DeepSeek Harness: the software-development methodology skills plus their session bootstrap, as a dsh plugin

DeepSeek Harness plugin for GPT models and Codex instructions, skills, plugin resources, and MCP configuration.

Per-project skill roots for DeepSeek Harness, with multi-level category discovery.

Turn code flows into source-linked Mermaid diagrams and interactive CodeWalkthrough explainers.

Superpowers skills for the DeepSeek Harness (dsh): a full engineering methodology served through dsh's own filesystem skill provider, with an always-on bootstrap.

Lists the skills in the shared skills directory with their source and version, installs and updates them from a GitHub repo, removes them to a recycle bin kept for 7 days, and controls which agents can see each skill and whether the model may invoke it.

Checks installed DSH plugins for version-declaration and API risks against the current host, with source locations when available, certainty, impact basis and coverage limits. Adds a compatibility settings panel, plugin-detail findings/badges, a compat_check agent tool and a skill provider.

A persistent multi-step task stack for DeepSeek Harness agents: focus_task / focus_complete / read_focus plus a /focus command, with zero automatic prompt injection

Read-only Skill inspector for DeepSeek Harness. It shows which Skills a conversation actually loaded — from observed loading evidence only — and which Skills the current environment can discover, and gives each Skill a detail page whose left column switches between the framework, the evidence, validation, evaluation, step evidence, run logic, the before/after of a modification when there is one, the definition facts and the raw SKILL.md. Declaration and run stay apart: the body is split into structure, declared workflow and progressive disclosure, the run logic is read from local receipts, and every declared step carries its own evidence — no observed evidence is reported as exactly that, not as executed or not executed, and the run's instruction hash sits beside the current definition as match, mismatch or unavailable. The evidence view gives each subject one of three states (declared, observed, unavailable), walks definition → load → use → outcome, names what each stage cannot reach, declines to attribute an outcome to the Skill, and can copy the snapshot out as byte-stable JSON. Validation checks the Agent Skills open standard and the platform profiles separately, each finding on a rule id and labelled standard compliance or platform compatibility. Evaluation keeps repeatable cases with the conditions each run was recorded under and the four stages of runtime evidence, comparing two runs of one case item by item without scoring them. The trigger boundary keeps should-trigger and should-not-trigger prompts, has you run them in a real new session, then records what was observed — whether a load record appeared and whether it was model-invoked or user-explicit; a typed /name is not a natural trigger, and an absent load record is reported as not observed, not as not triggered. The same projections are exposed to the agent as a read-only skill_review tool, which returns a structured review packet and says what it omitted when the packet will not fit whole. The inspector, the evidence chain and these reviews are computed on this machine from the definition and the session receipts; the Chinese reading version sends the body through the host's model when you ask for it, keeping code fences, paths and frontmatter verbatim and storing the result on this machine. A Skill can also be cloned into a local copy. It does not write back to the source Skill and does not run its scripts.

蒸馏主管（distillation-director）：把一本书蒸馏成可执行 Agent 技能的判态制元技能（V4.6：V4.3–V4.5 防坑体系与判官工作流之上，增 §21 **强制门禁**——gate_start 开工自证闸（手册哈希＋条款逐字抄录＋执行单＋机器层＋官方模板）／gate_stage 阶段依赖链（前阶段未过不得进入）／preflight 自动纳入活跃蒸馏任务）