delegate-deepseek-tasks

A workflow for assigning coding, review, testing, or documentation tasks to DeepSeek Worker, then checking the results before applying changes locally.

In plain words
What is it for?
It helps break work into tasks, delegate them without exposing secrets, inspect returned revisions, and apply only accepted changes.
Why use it?
It reduces the risk of accepting an outside worker's changes without reviewing their correctness, security, or fit with the project.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/prelearn-code/deepseek-mcp/delegate-deepseek-tasks
Any agent
npx skills add prelearn-code/deepseek-mcp --skill delegate-deepseek-tasks
Clone the repo
git clone --depth 1 https://github.com/prelearn-code/deepseek-mcp

Made for: Claude Code, Codex.

Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,365 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00109 $0.01365
Opus 5 $0.00055 $0.00682
Sonnet 5 $0.00022 $0.00273
Haiku 4.5 $0.00011 $0.00136

Measured 2d ago against content hash ed549a7d5d67, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

delegate-deepseek-tasks 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 2d ago.

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-deepseek-tasks/SKILL.md · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Delegate Tasks to DeepSeek

Use the primary GPT/Sol model as planner, integrator, and final authority. Use DeepSeek agents as isolated implementation workers. Never treat a worker result as trusted merely because its task completed or its internal tests passed.

Follow the workflow

1. Establish the local baseline

Inspect the repository and user request before delegating. Confirm:

  • the requested outcome and acceptance criteria;
  • the current Git state and relevant project instructions;
  • the files or modules that may change;
  • required tests and commands;
  • whether the task is read-only or authorizes implementation.

Do not submit secrets, credentials, private keys, environment files, customer data, or unrelated proprietary context to DeepSeek. Do not clean, reset, stash, or overwrite user changes to satisfy the worker's clean-worktree requirement.

Call the DeepSeek MCP capability and health tools when availability, limits, or Bridge compatibility are uncertain. Require a phase-2 Bridge with thinking/tool round-trip support for Agent Jobs.

2. Decompose the task in GPT/Sol

Create a small dependency graph before submitting work. Each delegated task must have:

  • one coherent outcome;
  • explicit acceptance criteria;
  • the smallest practical write_scope;
  • relevant validation commands;
  • enough context to work independently;
  • no responsibility for final integration or approval.

Prefer a single Agent Job when changes are tightly coupled. Split work when components can be implemented and tested independently. Do not fragment a simple change into many tiny tasks.

Classify dependencies:

  • Submit independent tasks together with submit_agent_batch.
  • Submit dependent tasks sequentially after the prerequisite result is reviewed and integrated.
  • Never run overlapping write scopes in parallel unless Sol intends to reconcile the conflicts manually.

Use the capability response rather than assuming fixed concurrency limits.

3. Choose model and task size

Read the full file on GitHub · 154 lines

Files

What ships with it

1 file 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. 2d ago First seen · 154 lines · 109 tokens per session scan A ed549a7d5d67

Subscribe to this mod's changes

delegate-deepseek-tasks is a skill published in the GitHub repository prelearn-code/deepseek-mcp (0 stars, last pushed 27d ago), licensed MIT. It adds 109 tokens to every session and 1,365 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.