DeepSeek Harness is an open-source framework for building and running AI agents, organized so that its functionality is provided through plugins. Developers use it to launch agent workflows through a local web interface or from source, while the catalogue add-ons extend the harness as plugins.
Borrowing it
Nothing to install: this file belongs to deepseek-ai/deepseek-harness. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/deepseek-ai/deepseek-harness/master/.agents/skills/dsh-translate-docs/SKILL.mdgit clone --depth 1 https://github.com/deepseek-ai/deepseek-harnessWrote 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/deepseek-ai/deepseek-harness/dsh-translate-docs)<a href="https://agentmods.dev/skills/deepseek-ai/deepseek-harness/dsh-translate-docs"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/dsh-translate-docs/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/deepseek-ai/deepseek-harness/dsh-translate-docs"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/dsh-translate-docs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00037 | $0.02317 |
| Opus 5 | $0.00018 | $0.01158 |
| Sonnet 5 | $0.00007 | $0.00463 |
| Haiku 4.5 | $0.00004 | $0.00232 |
Grade A, and why
dsh-translate-docs 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.
Copies of this mod
6 near-identical copies found in the catalogue:
- dsh-translate-docs — 100% identical, 2 lines differ
- dsh-translate-docs — 100% identical, 2 lines differ
- alego-translate-docs — 95% identical, 16 lines differ
- dsh-translate-docs — 92% identical, 6 lines differ
- dsh-translate-docs — 92% identical, 6 lines differ
- dsh-translate-docs — 92% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Translating DeepSeek-Harness docs
Invocation boundary
Run this extended workflow only when the user explicitly invokes dsh-translate-docs by name. Never select or load it for ordinary documentation work, from another skill, or from an inferred translation need; routine translation follows the one-shot, one-pass rule in docs/AGENTS.md.
What this skill is
This skill is guidance, not a translation memory. It is the workflow map for keeping foo.md ↔ foo.zh.md pairs consistent and natural in both languages. Both languages carry equal authority — a change is authored in either one, and that side is the source for that update. You are the translator: the rules below say what must hold, not how to phrase any particular sentence — phrasing judgment is yours, terminology is not.
Triage by change type — this decides everything else
- Update (pair exists, one side edited): follow the update path. It is briefing-driven and deliberately cheap: no guidance-corpus reading, no git archaeology, smallest counterpart edit. Never re-translate a whole document to apply an update — a minimal update preserves the reviewed phrasing of everything that didn't change; a re-translation throws that review away.
- New pair (no counterpart yet): follow the whole-document path.
- Deleted or renamed doc: delete or rename the counterpart and the
.i18n.yamlalongside it — the gate reports an incomplete pair otherwise.
Frozen Agent Notes under .agents/notes/archived/ are not translation work. Their complete triplets are sealed by the archive verifier; never update, re-record, or repair either side after archival.
The update path (briefing-driven)
The briefing-driven path matches guidance-corpus quality at a fraction of the cost; the archived briefed-updates Agent Note records the benchmark evidence.
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.
- 2d ago Changed 198f0edaed63
- 11d ago First seen · 75 lines · 37 tokens per session scan A e8585d8d2237
dsh-translate-docs is a skill published in the GitHub repository deepseek-ai/deepseek-harness (218,563 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 2,317 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.
Other skills, from other repositories
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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…
industry-research-method
A Chinese-language method for researching an industry by mapping its supply chain, tracking policies and news, and writing sourced reports. It separates the chain into upstream inputs, midstream production, and downstream distribution or use.
company-research-method
A documented process for researching a company using supplied files and selected public sources. It produces a company overview with business details, sourced financial figures, and stated risks.