dsh-failure-lens
Deterministic DeepSeek Harness Web client plugin that explains the Windows-sandbox `spawn EPERM` failure as a distinct Conversation Node.
141 results
Deterministic DeepSeek Harness Web client plugin that explains the Windows-sandbox `spawn EPERM` failure as a distinct Conversation Node.
Native Auto Review for DeepSeek Harness with automatic host compatibility selection
DeepSeek Harness bundle that routes real sandbox escalation prompts through a dedicated approval reviewer
Task-to-skill pairing with a laziness ladder and a safe install cellar. Never overpours, never serves untasted. DSH · Claude Code · Codex
Structured, machine-readable CI output for DeepSeek Harness (dsh): session event capture with JSON/NDJSON reports, JUnit XML, semantic exit codes, artifact collection and privacy redaction. Ships as a dsh profile bundle and a standalone CLI.
Fifth DeepSeek Harness mode with configurable Codex, Claude Code, or DSH audits, user-approved remediation turns, progressive Cordis/skill elevation, safety pauses, and Web/TUI review controls.
A DeepSeek Harness (DSH) plugin that adds an AI-adjudicated 'smart' approval mode: safe operations are auto-allowed via an isolated side-channel LLM judge, everything else falls back to the normal human approval popup.
DeepSeek Harness bundle that registers the skills-summarize-audit skill pack on ctx.skills.
Static and runtime security guard for the DeepSeek Harness: scans plugins and workspaces for malicious code, context injection and token waste (block/warn/clean), intercepts dangerous runtime tool calls and prompt steps, and exposes /scan, plugin_scan, the scan web panel and a user-managed allowlist. Fully static analysis — never executes scanned code.
Solve the AI goldfish brain: a personal memory layer for DeepSeek Harness — preferences, project conventions, workflows, and error lessons, stored locally as auditable, evidence-backed Markdown/JSON. 解决 AI 金鱼脑:偏好、项目约定、工作方式与纠错教训的本地可审计记忆层。
LLM pre-review for sandbox-escalation approvals: an independent-context LLM gate answers sandbox escalation requests before they reach the user, falling back to the user on any failure.
X-ray for your DeepSeek Harness — diagnostics for what's actually loaded, why, and what it costs: per-plugin context-tax attribution, per-request token ledger, skill catalog pricing, dependency cascades.
Scan installed DeepSeek Harness plugins and grade stability risk (hook surface, startup work, preflight health, packaging, dependencies). 扫描已安装插件的稳定性风险(钩子面/启动任务/预检/打包/依赖)。
Sessionless LLM sandbox approval reviewer for DeepSeek Harness.
GitHub App tools for WSL dsh: hint (env file existence) + repo PR/Actions status; never dumps secrets.
One-click health check & score for your DeepSeek Harness plugins. Scan → Score → Fix → Share. PerfScope for dsh.
Safe Git credential hints: GCM path, HTTPS vs SSH origin (never returns secrets).
AI response quality review for DeepSeek Harness: audits each finished assistant turn with an independent reviewer model and steers the agent to fix unreasonable output (up to 2 review rounds).
Evidence-backed application-security assurance for DeepSeek Harness
What can this MCP server actually do? Inspect its real capability surface, seal it, and get told when it changes. Never invokes a tool; gives the server a minimal environment.
依赖安全审计:扫描项目依赖的已知漏洞(OSV.dev)并检测过期依赖(npm registry),返回漏洞严重级/修复版本与升级幅度
Plug/unplug any DeepSeek Harness plugin cleanly: list every mounted layer, disable/enable without deleting, remove bundles + patch rows + dependencies in one pass, and audit for orphaned/dangling plugin state. Zero runtime dependencies; read-only by defau
Content-addressed proof that recorded DSH authorization decisions and effects agree
Pre-write reuse firewall for DeepSeek Harness: before the agent writes a new helper/service, surface the existing implementations that already cover that intent. Deterministic retrieval (no LLM) backed by the Auto_code_audit capability channel.