Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tonytanglab/deepseek-harness-relay-mcp --skill delegate-to-deepseek-harnessgit clone --depth 1 https://github.com/tonytanglab/deepseek-harness-relay-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness)<a href="https://agentmods.dev/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness"><img src="https://agentmods.dev/badge/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness"><img src="https://agentmods.dev/badge/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.03572 |
| Opus 5 | $0.00047 | $0.01786 |
| Sonnet 5 | $0.00019 | $0.00714 |
| Haiku 4.5 | $0.00009 | $0.00357 |
Grade A, and why
delegate-to-deepseek-harness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegate to DeepSeek Harness
Use DSH Relay to dispatch bounded analysis or workspace changes to a DeepSeek Harness model, keep wait_run until a terminal status whenever this task must consume the result, and independently verify that result. Sharing webUrl is not completion.
Permission mode
- Use
start_reviewfor analysis, diagnosis, research, comparison, planning, and code review. This is the default when no file change is requested and is fixed toread-only. - Use
start_runwithpermissionPreset: workspace-writeonly when the user explicitly delegates implementation or asks Harness to modify the registered workspace. Ordinary fixes, edits, refactors, tests, and generated workspace files belong in this mode. - Do not use
danger-full-accessfor ordinary workspace changes. Use it only when a necessary action is outside the registered workspace or otherwise requires that native preset, the action remains within the user's request, and the user has explicitly confirmed the elevated risk. PassconfirmedDangerousPermission: trueonly after that confirmation. - A request to call Harness is not by itself authorization to edit files. Infer write authorization only from an implementation request such as “让 Harness 修复/修改/实现”, or obtain it before dispatch.
Required setup
- Read the target repository's
AGENTS.mdbefore dispatch. - Prefer the official
@deepseek-ai/dsh-relaybundle in the Harnesswebprofile. External agents should launchdsh-relay-proxy, which discovers the active internal authority from$DSH_HOME/plugins/dsh-relay/<profile>/relay-endpoint.json; do not copy a bearer token into client configuration. - Prefer DSH Relay MCP tools for service connection, model selection, prompt submission, status checks, cancellation, and result collection. Use Browser only to verify or present the Harness conversation.
- Invoke Relay operations only through the native MCP tools exposed by the installed plugin. Never generate or run temporary JavaScript/TypeScript files such as
.tmp/harness-*-call.mjs, and never usenode, PowerShell, Python, a terminal, or another shell client to call or poll Relay RPCs. Shell fallback bypasses the managed background transport and can open visible console windows on Windows. - If the native Relay MCP tools are unavailable, stop the delegation attempt, diagnose or reinstall the plugin, and continue from a new Codex task after the updated plugin is loaded. Do not simulate missing tools with an ad hoc client process. Ordinary local verification commands may still run in the Codex terminal, but they must not be used as a Relay RPC transport.
- Do not impose a blanket offline restriction. Let Harness decide whether task-relevant public network research is needed, including public GitHub repositories, official documentation, and ordinary webpages. Keep research within the delegated scope, prefer primary sources, and require URLs for material external claims. Network research does not authorize account sign-in, credentials, private services, source uploads, external writes, messages, pushes, or broader filesystem permissions. If the selected Harness preset cannot access the network, report that limitation instead of escalating to
danger-full-accesssolely for research. - Route capability and permission needs back to the calling Codex agent for decision instead of treating them as absolute prohibitions or waiting indefinitely inside Harness. This includes deletion, file replacement, image or other media generation, tools unavailable in the selected preset, and operations requiring a different permission boundary. State the exact action, targets, reason, risk, and least-privilege alternative. The calling agent should resolve ordinary reversible in-scope actions under the user's existing authorization without asking again; escalate to the user only when platform policy requires it or the action is materially destructive, irreversible, credential- or private-account-sensitive, externally consequential, or outside the authorized scope.
- Treat an explicit request for Harness or a named Harness model to review the current or named registered workspace as authorization for Harness to read that in-scope workspace itself. The calling task sends only the authorized workspace, file or directory locations, review or implementation scope, acceptance criteria, and routing/permission metadata. Harness must read the files through its authorized workspace tools. Never read or serialize source merely to paste source text, diffs, file dumps, encoded source, or repository archives into
task, textcontent,steer_run, orreply_runarguments. Do not ask for redundant per-file approval merely because the repository is private. This authorization excludes credentials, secrets, unrelated paths and edits. - When the current conversation explicitly asks to use Harness, pass
authorizationBasis: explicit-user-requesttostart_review,start_run, orreply_run. This is truthful evidence for Codex approval review; it does not broaden the workspace, task scope, permission preset, provider destination, or allowed external actions, and it cannot guarantee approval. Do not set it for inferred or background delegation. - Separate the review subject from its supporting read context. When the review target is a plan or other document, Harness may search and read related implementation, tests, configuration, and architecture material inside the explicitly authorized
contextReadScopeto verify that document.reviewTargetsis not a read whitelist. SetcontextReadScopeequal to the target paths only when the user explicitly requests a target-only review. - Apply the same path-reference-only transfer contract to
read-onlyand every write-capable permission mode.workspace-writeauthorizes Harness to modify only the named workspace paths; it does not authorize the calling agent to embed source text in task parameters. A generic request to call Harness remains read-only unless the user also requests implementation. - Treat
reviewTargets,contextReadScope,excludedPaths, andwriteScopeas task instructions in addition to Harness native permissions. They do not implement per-path filesystem isolation. The selected model may send content it reads to its configured provider; a loopback Relay address describes the control connection, not all downstream model processing. - Exclude credentials, secrets, browser storage, model files, production data, unrelated user files, and direct modification of
.gitinternals. - Treat the Harness workspace registry, not
host.describe.cwd, as the default routing authority. Explicit Relay roots remain an additional strict boundary. - Preserve all pre-existing user changes. Record the initial worktree state before a write run so Harness changes can be distinguished from earlier edits.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed · +5 lines 9cb53ec5ae3d
- 7d ago Changed · +11 lines f07f53c3fbd2
- 12d ago First seen · 76 lines · 94 tokens per session scan A d6c09bd8e866
delegate-to-deepseek-harness is a skill published in the GitHub repository tonytanglab/deepseek-harness-relay-mcp (3 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 3,572 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
dsh-web-skin-developer
Build a new skin for the dsh-web skin collection (DSH Web GUI) and publish it into the Skin Center — the first-level settings section — scaffold with scripts/dsh-skin-new, author the v2 skin.json manifest plus skin.css token remap (pure asset directory, no package.json, no build step), validate with scripts/dsh-skin…
manage-taskboard
Manage work in the native DeepSeek Harness Taskboard with exact task ids and optimistic versions. Use when an Agent must inspect project work, claim an eligible todo, record progress or blockers, verify an implementation, submit it for human review, or release its own claim; also use when a human asks how to accept…
figma-code-connect
Creates and maintains Figma Code Connect template files that map Figma components to code snippets. Use when the user mentions Code Connect, Figma component mapping, design-to-code translation, or asks to create/update .figma.ts or .figma.js files.
yao-ocr
OCR text recognition expert. ALWAYS invoke this skill when you need to extract text from images or PDFs — including invoices, receipts, ID cards, bank cards, business licenses, tables, handwritten documents, or any visual text content.
yao-workspace
Workspace file I/O expert. ALWAYS invoke this skill when you need to list workspaces, read or write files in a workspace on a remote node, or browse workspace directories. Use this for cross-node file operations — for local sandbox files, use standard filesystem tools instead.
xhs-ops-worker
Execute authorized Xiaohongshu publishing, comments and replies from iPolloWork Schedule or a project session using the selected account's persistent browser.