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-pr-description/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-pr-description)<a href="https://agentmods.dev/skills/deepseek-ai/deepseek-harness/dsh-pr-description"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/dsh-pr-description/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-pr-description"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/dsh-pr-description.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 | $0.00070 | $0.04266 |
| Opus 5.5 | $0.00028 | $0.01706 |
| Sonnet 5.5 | $0.00014 | $0.00853 |
| Haiku 4.5 | $0.00007 | $0.00427 |
Grade A, and why
dsh-pr-description 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.
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.
How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing PR descriptions
This skill defines what a deepseek-harness PR description contains, how to write it, and when to update it. The PR template supplies only the section headings and placeholders; this skill owns the requirements for each section. Every PR description follows this skill, including PRs created with gh pr create --body-file, which skips the template.
Scope
- Write the complete description when you create the PR.
- After the PR exists, update the affected sections when the description no longer matches the PR, at times you judge suitable.
- Each PR in a stack has its own description, which covers only that layer's changes against its base branch.
Description structure
The description uses four second-level headings, in this order: ## Motivation, ## Changes, ## Testing, and ## AI Usage.
Write fixed section headings and labels, such as Interface changes, Behavior changes, Test design, and Test entries, in English. Write table headers and the rest of the description in the PR description's language, Chinese unless a human asked for another language.
Motivation
- State the problem in one sentence.
- Reference at least one same-repository Issue: use
Fixes #N,Closes #N, orResolves #Nwhen the PR resolves it, andRefs #Nwhen it only gives context. PR numbers do not count as Issue references, and neither do references inside HTML comments, code fences, or inline code. Issue management owns the exact rules and the Priority matching.
Changes
- Interface changes: summarize changes to commands (including repository scripts), flags, configuration keys, environment variables, public exports, plugin registration values, protocols, or persisted formats; write None when there are none.
- Behavior changes: summarize results that users, models, developers, or the system can observe, including defaults, performance, timing, and output; write None when there are none. Changes to documentation and agent instructions, such as READMEs, AGENTS.md, and skills, are behavior changes for the readers they guide.
- State only behavior that the diff guarantees and the tests cover.
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.
- yesterday First seen · 205 lines · 70 tokens per session scan A bb5d25480625
dsh-pr-description is a skill published in the GitHub repository deepseek-ai/deepseek-harness (260,751 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 4,266 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-24.
Other skills, from other repositories
triage
Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.
code-review
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use…
improve-codebase-architecture
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
manage-taskboard
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.