Plugins

Blocks AI coding agents from editing files without evidence and from running unapproved high-risk commands, and tells quoted dangerous strings apart from commands actually being executed.

Exposes the Paper-gogo evidence-first paper workflow as native tools: all 18 phases and the seven G0-G6 gates become callable, gate results are normalised and advancement is refused while any gate fails, and claims are audited against the four evidence states SUPPORTED, INFERRED, VERIFY and MISSING. Ships the workflow text and 57 skills in its own directory, so it installs without a separate Paper-gogo package.

DSH self-discipline companion with recurring tasks, a gaze-tracking desktop mascot, evidence logs, final AI review, reminders, and window intervention on Windows and GNOME Wayland.

Clusters arXiv, first-party lab, official artifact, hardware-vendor, and opt-in X signals into versioned release evidence bundles, then gates claim-level reproduction on commands, artifacts, metrics, and verifiers.

Cordis-native, evidence-driven full-stack engineering workflow: inspect-first planning, explicit verification evidence, and approval-aware gating for sensitive operations.

21 read-only lifecycle governance tools in one self-contained DSH plugin: task tiering, state/plan/evidence validation, gate precheck and aggregation, release/install audits, context and progress analysis, critical path, resume reconciliation, and a mutation preview that always denies execution. Installs from npm as @240xu/dsh-tech-lead.

DSH plugin that registers the ai-eight-honors-eight-shames skill: eight checkable working rules for coding agents (verify before calling, confirm ambiguity, cite evidence, reuse before creating, test before claiming done, follow local conventions, separate fact from inference, keep changes reversible) plus a ninth rule that logs each user request and the change made in two fixed report files at the workspace root.

Cross-session experience memory for DSH. Lessons are evidence-graded, injected when the turn is about the same thing, and shown just before an action only when the record declares which call it applies to. A rule that holds whatever the turn is about — "always answer in Chinese" — can be marked **standing** and is then carried every turn: measured on 24 isolated real-model turns, a standing rule is followed 6/6 against 0/18 for the controls (empty store, same record unmarked, unrelated standing record). A guess still cannot become always-on: a standing record needs a verified passage like any other. What nobody looks up is retired, reversibly. Five tools, seven slash commands, zero runtime dependencies.

DSH plugin for bounded agent evaluation: compare an original with candidate prompt or supported configuration changes against user-supplied checks, record evidence and costs, and leave adoption to the user.

Live Android device pane next to your DSH conversation: scrcpy H.264 streaming, agent taps verified by screenshots and a UI tree, and screenshots / recordings / debug evidence saved into one host directory. Debug sessions keep segmented video, full logcat and per-action frames. Emulators and USB phones, human+agent co-operation, loopback-only.

Evidence-governed experience memory for DeepSeek Harness

Combines fault knowledge-base symptom-to-cause rules with similar past cases to rank candidate motor diagnoses with evidence terms and suggested extra tests.

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.

Whole-book translation production line for DeepSeek Harness: deterministic chapter detection and segmentation, per-chapter subagent translation, glossary control, full-book review, targeted revision, and auditable meta.json evidence.

Pre-install static audits for npm-installable DSH plugins; emits and validates the open `dsh-vet/v1` report with severity, confidence, evidence, derived grades, a CI Action, and auditable badges.

Actionable quality diagnostics for DSH agent sessions, with tool-call evidence and next-step recommendations.

Evidence-first GitHub research subagent with bounded tools and in-memory request caching.

An approval-gated OME engineering delivery preset with session-isolated lifecycle evidence.

Conversation-level multi-agent workbench for editable task planning, real child-session observation, plan-versus-runtime comparison, and evidence-backed recovery previews; tested with DSH 0.1.1-rc.2.

Slash commands ported from other coding agents (setup, connect, install, trust, browse, doctor, status, model, memory, compact, resume, review, mcp, init, suggest, improve, refactor), a zero-dependency static scanner for plugin source, and an in-repo catalog of audited plugin report cards that cite file-and-line evidence.

21 read-only lifecycle governance tools in one self-contained DSH plugin: task tiering, state/plan/evidence validation, gate precheck and aggregation, release/install audits, context and progress analysis, critical path, resume reconciliation, and a mutation preview that always denies execution. Installs from npm as @240xu/dsh-tech-lead.

Reliable todo panel that survives restarts (official panel only re-renders on write — fixed via projection pre-warm) with three-state completion verification: evidence exists → verified, fake evidence → blocked, no evidence → unverified badge; settings toggle to fall back to official behavior.

Local, auditable personal memory for DeepSeek Harness: preferences, project conventions, workflows and error lessons persisted as a changelogged JSON file in the workspace, with onboarding, auto project-convention extraction and evidence-backed lessons.

Replay real DeepSeek Harness turns against Standard, Minimal, Anchored, or plugin candidates with frozen request-surface evidence