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 knopki/agent-skills --skill deepseek-promptgit clone --depth 1 https://github.com/knopki/agent-skillsWrote 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/knopki/agent-skills/deepseek-prompt)<a href="https://agentmods.dev/skills/knopki/agent-skills/deepseek-prompt"><img src="https://agentmods.dev/badge/skills/knopki/agent-skills/deepseek-prompt/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/knopki/agent-skills/deepseek-prompt"><img src="https://agentmods.dev/badge/skills/knopki/agent-skills/deepseek-prompt.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 | $0.00084 | $0.05712 |
| Opus 5 | $0.00042 | $0.02856 |
| Sonnet 5 | $0.00017 | $0.01142 |
| Haiku 4.5 | $0.00008 | $0.00571 |
Grade A, and why
deepseek-prompt scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- For a fix: `curl … ; expect { "ok": true }` How it starts
The opening of the file, as written. The whole thing — 516 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepSeek Prompt Skill
Overview
Build prompts that play to DeepSeek V4's strengths and avoid its known failure modes: commentary instead of execution, roleplay-style thinking (internal monologue, parenthetical asides), mode collapse, and weak discipline injection.
This skill operates in two lanes (how you use it):
- Interactive mode (prompt is for the end user in this session): run the interrogation in §3 — collect the info the user has, then fill the template.
- Subagent / autonomous mode (prompt will be sent to a DeepSeek subagent or a fresh DeepSeek session): decide the content yourself from available context — do NOT interrogate the user. Use §4.
Separately, DeepSeek V4 itself has three thinking modes you can force by appending a Chinese instruction block — Default / Pure Analysis / Role Immersion. That is the prompt-injection mechanism this skill relies on; see Three thinking modes — when and whether to inject below.
Decide the mode from how the request is phrased:
- "write me a prompt for DeepSeek to do X" / "I want to prompt DeepSeek to…" → interactive.
- "launch a subagent to do X on DeepSeek" / "prepare a prompt for the DeepSeek
agent" / the prompt is a parameter you pass to a
Task/Agentcall → subagent mode.
If the intent is ambiguous, ask one clarifying question: "Is this prompt for you to send into a DeepSeek session yourself, or should I write it as a subagent/Agent task prompt?" — then proceed.
When to Use
Trigger this skill whenever you are about to produce a prompt whose target
runtime is a DeepSeek model (deepseek-v4-pro, deepseek-v4-flash in API or
Expert Mode). Concretely:
- The user asks you to "write / draft / compose a prompt for DeepSeek", "make a prompt for DeepSeek", "format this task for DeepSeek".
- You are composing the
prompt:argument of atask()/ subagent call that will run on a DeepSeek model. - You are translating a vague user request into a clean DeepSeek task spec.
Do not trigger this skill for non-DeepSeek models. The injection block works on API + Expert Mode only; DeepSeek Web Quick Mode ignores it — don't promise its effect there.
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.
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.
- 12d ago First seen · 516 lines · 84 tokens per session scan A d5bd7012a463
deepseek-prompt is a skill published in the GitHub repository knopki/agent-skills (2 stars, last pushed 10d ago), licensed MIT. It adds 84 tokens to every session and 5,712 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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