最新资讯
dev.to 你的 Agent Harness 应具备的 17 项能力 dev.to 离线 AI 记忆中 0.8 余弦阈值为何失效 dev.to Kimi K3.1 Pro 开放权重:自托管 2.8T 模型前的开发者清单 dev.to 如何通过工具调用引导模型以提升 Harness 质量 dev.to AI Agent 审计轨迹不等于对话记录 dev.to 精简 MCP server 工具数量:更少工具、更小影响面,双重收益 dev.to 为什么 git checkout 无法撤销 AI 编码 agent 的改动? wechat AI短剧门槛降降降!实测即梦短剧工作室:剧本分镜预演一条龙,伙伴计划长期护航 dev.to 让模型改写文档前,先量化事实保真度 dev.to 回放 153 个 Claude Code 与 Codex 会话,审计 Agent 的生产影响范围 dev.to 银行 77 意图分类最便宜 LLM:GPT-6.1 Terra 每次成功任务 $0.000727 theinformation.com Chesky的副业:Airbnb向CEO新设AI实验室出售IP
多元动态
登录 注册
AI编码 dev.to · @Vitaliy Ryumshyn

实测 DeepSeek Harness 一周:产出一个已发布插件,API 成本为 0

原文 我的收藏

作者以评审者身份试用 DeepSeek Harness 一周后成为其插件作者。该工具强调“一切皆插件”:Agent 自带 Web UI 以插件包形式提供,模型选择与配置界面由插件贡献组装,可选的 Codex、Claude Code 子代理也以插件形式加载,均通过 manifest 和扩展 API 接入。作者以在 harness 内构建定价看板作为测试项目。

AI推荐理由 作者以一周实测 DeepSeek Harness 并产出插件为线索,描述其“一切皆插件”的扩展架构(Web UI、模型设置、子代理均以插件形式加载),对 Agent 框架设计有参考价值;但属个人体验,缺少性能与稳定性数据,且 API 成本为 0 的表述未说明条件。

74

正文

I tested DeepSeek Harness for a week. I left with a shipped plugin and $0 in API costs I came to DeepSeek Harness as a reviewer and left as one of its plugin authors, which is a fair measure of how the week went. The hook is on the repo's first line: "Everything is a plugin." Not the usual marketing meaning — not a config file with a couple of third-party hooks. In DSH the agent hosts its own web UI as plugin packages; the settings screen where you pick and configure models is assembled from plugin contributions (this is the part I verified the hard way); even the optional subagents — Codex, Claude Code — ship as plugins you can add or drop. All of it loaded through manifests over a real extension API. I've poked at a lot of "extensible" tools. This one takes it literally, and poking at it turned into the most fun I've had with an agent harness in a while. The test project: a pricing board inside the harness itself The gap I kept feeling in Settings → Models was the two questions I ask before switching providers every time: what does this model actually cost per million tokens, and is a cheaper route to the same model available? DSH tells you which models exist. It doesn't tell you what they cost. dsh-model-pricing closes that, and it lives inside the harness's own Settings page — because that's the point of testing the plugin system: per-1M-token input / output / cache prices for 7,178 priced models across 213 providers (models.dev data) the harness's own routing catalog overlaid for the 788 models it can actually invoke — where the two sources disagree, the row is flagged with ⚠ rather than silently averaged same-model, cross-provider comparison with a cheapest badge: GLM-5.2, say, runs from $3.08 to $4.84 per 1M output tokens depending on the gateway — the same model, 57% apart capability tags (coding / agentic / vision / long context / open weights) computed from structured catalog fields, with a user-configurable rule engine subscription plans (Coding Plan, Token Plan) grouped separately and excluded from per-token ranking a community promotions feed — the part I most want to tell you about, below English + Chinese UI (the platform's) plus a Russian pack the plugin itself registers It installs through the harness's own plugin manager — I never forked anything: npx -y @deepseek-ai/dsh plugin --profile web add dsh-model-pricing Enter fullscreen mode Exit fullscreen mode What surprised me: I built it on a free model Here's the part I didn't expect. I built the whole thing using DeepSeek Harness, driven by Qwen3.8-Flash through B.AI's current promotion — the one the plugin itself ships as a record: "Qwen3.8-Flash API at 0 Credits (free)," with a source link, a verification date and "end not announced" stamped in. Total LLM spend for the project: $0. Which made the week a perfect loop — an agent harness, used to build a plugin about the economics of agent harnesses, on a free model the plugin advertises. Eight records shipped on day one; one of them describes the free model that wrote this plugin's UI. Numbers, since the internet likes them priced rows / providers 7,178 / 213 harness-catalog overlaid rows 788 (30 disagreements flagged, not averaged) plan rows grouped & excluded from ranking 175 promo records at launch 8 (each with source URL + verification date) commits / files / LOC 28 / 18 / ~2,300 wall-clock ~22h, incl. overnight autonomous rounds LLM cost $0 — free API promotion, re-verify date 2026-10-10 UI languages en + zh (platform), ru (plugin) Try it — as reviewer and as builder If you're curious about DeepSeek Harness the way I was: run it, then break into its settings page. The architecture is the product; the agent is very good at both jobs, even on a model that costs nothing. npx -y @deepseek-ai/dsh plugin --profile web add dsh-model-pricing Enter fullscreen mode Exit fullscreen mode Repo (docs, feature map, the promotion contribution rules — all public): github.com/vitas/dsh-model-pricing · npm: dsh-model-pricing · Apache-2.0.

来源报道 · 1 篇 · 以下链接均前往原始媒体

← 返回精选动态 原文

更多内容