delegate-to-deepseek-harness

delegate-to-deepseek-harness is a skill for Codex from tonytanglab/deepseek-harness-relay-mcp. It costs 94 tokens per session (3,572 once invoked), scanned A, original, MIT.

A skill for sending a clearly defined local task to a DeepSeek model through Harness and tracking its result. It distinguishes read-only reviews from tasks allowed to change workspace files.

In plain words
What is it for?
Use it for code reviews, diagnosis, planning, comparisons, fixes, edits, refactors, tests, or generated workspace files when the user delegates the work.
Why use it?
It gives delegated work explicit boundaries, so analysis and file changes are not mixed up and results can be checked afterward.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions AGENTS.md; mentions Codex.

Good fit Use it for code reviews, diagnosis, planning, comparisons, fixes, edits, refactors, tests, or generated workspace files when the user delegates the work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness
Install

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.

Any agent
npx skills add tonytanglab/deepseek-harness-relay-mcp --skill delegate-to-deepseek-harness
Clone the repo
git clone --depth 1 https://github.com/tonytanglab/deepseek-harness-relay-mcp

Made for: Codex.

Wrote 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.

agentmods badge for delegate-to-deepseek-harness

README.md
[![agentmods](https://agentmods.dev/badge/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness/github.svg)](https://agentmods.dev/skills/tonytanglab/deepseek-harness-relay-mcp/delegate-to-deepseek-harness)
Your own site
<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.

agentmods 80×15 button for delegate-to-deepseek-harness

Your own site · 80×15
<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>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,572 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash 9cb53ec5ae3d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/build_task_manifest.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/delegate-to-deepseek-harness/SKILL.md · 92 lines

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_review for analysis, diagnosis, research, comparison, planning, and code review. This is the default when no file change is requested and is fixed to read-only.
  • Use start_run with permissionPreset: workspace-write only 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-access for 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. Pass confirmedDangerousPermission: true only 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.md before dispatch.
  • Prefer the official @deepseek-ai/dsh-relay bundle in the Harness web profile. External agents should launch dsh-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 use node, 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-access solely 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, text content, steer_run, or reply_run arguments. 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-request to start_review, start_run, or reply_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 contextReadScope to verify that document. reviewTargets is not a read whitelist. Set contextReadScope equal to the target paths only when the user explicitly requests a target-only review.
  • Apply the same path-reference-only transfer contract to read-only and every write-capable permission mode. workspace-write authorizes 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, and writeScope as 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 .git internals.
  • 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.

Read the full file on GitHub · 92 lines

Files

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.

Changes

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.

  1. yesterday Changed · +5 lines 9cb53ec5ae3d
  2. 7d ago Changed · +11 lines f07f53c3fbd2
  3. 12d ago First seen · 76 lines · 94 tokens per session scan A d6c09bd8e866

Subscribe to this mod's changes

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.

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