deepseek-automation

deepseek-automation is a skill for Codex from zhu1090093659/deepseek-pp. It costs 42 tokens per session (1,767 once invoked), scanned A, original, Apache-2.0.

Project-specific guidance for implementing and maintaining DeepSeek++ automations that start in a new chat session and continue on a schedule.

In plain words
What is it for?
Use it to resume, review, implement, or verify the DeepSeek++ automation feature while following its project documentation and GitHub issue process.
Why use it?
Automation work spans scheduling, browser communication, documentation, and issue tracking, so changes can easily go in the wrong part of the project.

Skill for Codex

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

Good fit Use it to resume, review, implement, or verify the DeepSeek++ automation feature while following its project documentation and GitHub issue process.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zhu1090093659/deepseek-pp/skill
About the project

DeepSeek++ is a browser extension that turns the DeepSeek website into an AI workspace with tools, memory, skills, media analysis, and automation. DeepSeek users employ it to manage projects, control browser pages, search the web, reuse context, and export conversations, while the catalogue entries add skills and instructions for that workspace.

zhu1090093659/deepseek-pp · 1,818 stars · on GitHub · chromewebstore.google.com

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 zhu1090093659/deepseek-pp --skill skill
Clone the repo
git clone --depth 1 https://github.com/zhu1090093659/deepseek-pp

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 deepseek-automation

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhu1090093659/deepseek-pp/skill/github.svg)](https://agentmods.dev/skills/zhu1090093659/deepseek-pp/skill)
Your own site
<a href="https://agentmods.dev/skills/zhu1090093659/deepseek-pp/skill"><img src="https://agentmods.dev/badge/skills/zhu1090093659/deepseek-pp/skill/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 deepseek-automation

Your own site · 80×15
<a href="https://agentmods.dev/skills/zhu1090093659/deepseek-pp/skill"><img src="https://agentmods.dev/badge/skills/zhu1090093659/deepseek-pp/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,767 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 117
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
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 $0.00042 $0.01767
Opus 5 $0.00021 $0.00883
Sonnet 5 $0.00008 $0.00353
Haiku 4.5 $0.00004 $0.00177

Measured 10d ago against content hash d438881339d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

deepseek-automation 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 10d 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.

docs/archives/deepseek-automation/skill/SKILL.md · 186 lines

How it starts

The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DeepSeek Automation

Use this project-local skill for the DeepSeek++ automation implementation. The feature goal is: create Codex-style automations that can run immediately in a new DeepSeek chat session and then continue in that same automation session on a cron/RRULE-like schedule.

Start Every Session

  1. Read docs/progress/MASTER.md.
  2. Confirm tracking mode. Current mode is GITHUB_STANDARD.
  3. Query GitHub before starting work:
gh issue list -R zhu1090093659/deepseek-pp --label "spec-driven" --state open --json number,title,labels,milestone
  1. Pick the next open issue in dependency order unless the user names a task.
  2. Read the selected Issue body and linked local docs under docs/analysis/ and docs/plan/.
  3. Update docs/progress/MASTER.md Current Status at session start and end.

Architecture Rules

  • Keep scheduling in background code.
  • Keep actual DeepSeek request execution in the DeepSeek page main-world context.
  • Use content script only as a narrow bridge between background and main world.
  • Do not add automation business logic directly into fetch-hook.ts unless the task is explicitly about hook compatibility.
  • Prefer new focused files under core/automation/.
  • Do not rely on background-only fetch('/api/v0/chat/completion') for MVP; DeepSeek web completion has challenge/proof-of-work behavior.
  • Preserve existing memory, skill, preset, and tool-call behavior unless the Issue explicitly changes it.

DeepSeek Web Facts

Verified on 2026-05-21:

  • Completion endpoint: /api/v0/chat/completion.
  • History endpoint: /api/v0/chat/history_messages.
  • Completion request fields include chat_session_id, parent_message_id, model_type, prompt, ref_file_ids, thinking_enabled, search_enabled, action, and preempt.
  • New session and same-session continuation work from the web UI.
  • Reload restores the automation test session from history.
  • Persist the latest valid parent message id after every run and reconcile it against history.

Read the full file on GitHub · 186 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. 10d ago First seen · 186 lines · 42 tokens per session scan A d438881339d0

Subscribe to this mod's changes

deepseek-automation is a skill published in the GitHub repository zhu1090093659/deepseek-pp (1,818 stars, last pushed 27d ago), licensed Apache-2.0. It adds 42 tokens to every session and 1,767 once invoked, about $0.0002 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 2026-08-30.

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