Plugins

Automatisierte tägliche Content-Pipeline für Insta360 GO 3S: BLE/WiFi-Fernaufnahme von Aquariumaufnahmen, drahtloser Import, ffmpeg-Qualitätsbewertung mit Entscheidungsprotokoll, automatische Bearbeitung (Segmentauswahl, TTS-Erzählung, Musik, Untertitel) und Bilibili-Upload über biliup (standardmäßig Trockenlauf).

Host-Plugin Kimi WebBridge für DeepSeek Harness: Modellwerkzeuge, die den ECHTEN Browser des Nutzers steuern (Navigieren, Snapshot, Klicken, Ausfüllen, Auswerten, Screenshot, Netzwerkprüfung, Verwaltung der Tabs) über den lokalen Daemon kimi-webbridge

Lokale semantische Suche im Code für DeepSeek Harness: symbolbewusste Indexierung auf Ebene der Fragmente, lexikalische Embeddings offline oder ein zu OpenAI kompatibler Endpunkt und hybrider Abruf aus Vektoren und BM25, fusioniert mit RRF – drei dsh-Werkzeuge plus eine CLI sema.

Entscheidungs- und Zielgedächtnis mit Linie: explizite Befehle und ein Modell-Tool erfassen Entscheidungen deterministisch, eine Status-Karte verankert sie über die Compaktion hinweg neu, ein verlustfreier Ereignisstrom mit BM25+jieba-Suche stützt dies, und eine Fidelity-Regressionssuite auf Szenarioebene schaltet Releases frei.

Nativer Side-by-Side-Chat neben der Hauptunterhaltung: eine unabhängige archivierte DSH-Sitzung mit vollständiger nativer UI, Bedarfsabruf des Elternkontexts, Auswahlzitaten und Behalten-oder-Löschen-Lebenszyklus.

Führt reproduzierbare DSH-Profil- und Patch-Experimente mit geführter Fallausarbeitung, Assertions, Web-Vergleichsberichten, Wiederherstellung und Richtlinienprüfungen aus.

30 klassische Open-Source-Theme-Paletten (Catppuccin, Nord, Tokyo Night, Gruvbox, Solarized usw.), abgebildet auf offizielle ThemeService-Tokens für DeepSeek Harness, mit einem Style-Settings-Panel für Live-Anpassungen von Farbe/Schrift/Radius und JSON-Export/-Import zum Teilen von Konfigurationspaketen.

Untersucht vor der Entwicklung lokalen Code sowie GitHub/npm nach wiederverwendbaren Implementierungen, bewertet Wiederverwendung versus Neuschreiben und prüft die Architekturkopplung.

Scannt die für die aktuelle Sitzung sichtbaren Skills und ordnet sie nach Relevanz für das jüngste Gespräch.

Ein modell-natives Meta-Agent-Plugin für DeepSeek Harness: Das Modell synthetisiert zur Laufzeit aufgabenspezifische Workflows aus fünf agentischen Workflow-Mustern (Prompt Chaining, parallele Worker, Router, Supervisor, Evaluationsschleife) und koordiniert Tools und Subagent

Erstellt prüfbare Wissensdatenbank-Pakete (SQLite FTS5) aus md/txt/docx/pdf mit deterministischem Retrieval und Lesen des Originaltexts.

Prior-art search for an idea: three tools find similar open-source projects on GitHub, rank them by a score computed in code from a relevance judgement and the star count, then read the chosen repositories (README, dependency manifest, directory tree, key files) and report the class and function declarations found in each file header; files_read lists what was actually fetched.

All-in-one local memory: JSONL files per scope (session, project, global, or a custom name) with per-scope dedup, four model tools (memory_save, memory_search, memory_list, memory_forget), automatic recall injected into agent pre-step, and a settings panel. Retrieval combines lexical IDF with a local embedding backend, which the panel can install and manage itself.

Routes DSH web search through the current session's model and a self-hosted retrieval backend.

A Cyrene-themed agent for DSH, with a customizable look (palette, wallpaper, particle effects, background music, typing sound) and a code security scan. It carries a worldbook, long-term memory and a speech-style correction layer (every reader gets their own Cyrene), plus retrieval over the script to back up its answers.

Cross-compaction memory for a long session: on compaction it stores what is being dropped, and at question time it injects a few relevant passages (or nothing) so the model can recall what you decided before.

Memory-assembly team for DeepSeek Harness: every message triggers a five-step cognition loop (judge, retrieve, assemble, feedback, calibrate) carried by role-playing subagents (judge, retriever, archivist, advocate, editor, scribe), using BM25 retrieval, time-ordered material, and LLM assembly to build useful material packs injected into linghun. Works with dsh-linghun.

Turns a local Obsidian vault into a dedicated RAG chat panel: a sidebar page with the note browser, the retrieval-augmented chat and the cited source side by side, answering from fully local BM25 plus CJK-bigram retrieval over your notes and streaming through the DSH model channel, with clickable \[n] citations and mtime-based incremental indexing.

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.

Reflect2Evolve memory plugin: layered L1/L2/L3 memory, reflection-weighted value backprop, cross-task policy induction, skill crystallization, and three-tier retrieval for OpenClaw, Hermes Agent, and DeepSeek Harness.

Windows system-drive (C:) cleanup for DSH: rule-based scan, five-tier safety grading, a staging area with a rollback ledger, UAC elevation, and migration to another drive — a model tool plus a Web GUI panel.

Language-pack framework that rewrites model replies: A is an independent LLM rewrite, B injects FTS5 terminology retrieval into that rewrite, C applies local dictionary and regex rules, and composite runs a pipeline such as B then A then C. Ships a GitHub pack marketplace, a ZIP installer with path, size and file-type checks, and a mandatory risk disclaimer gate.

Persistent project intelligence and memory plugin for DSH: architecture analysis, cross-session context, TODOs, and optional hybrid retrieval

Compares existing DSH sessions or runs controlled A/B trials between agent presets, showing aligned timelines, paired metric deltas, explicit success checks, and exportable reports.