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Fork Night

Kimi K3 is the Night Watch’s brain

A creative co-pilot at your desk. A planner while you sleep. Here’s how Kimi turns a story brief into a plan you can build on.

Watch the walkthrough

Three jobs, one model

Kimi K3 (by Moonshot AI) via TokenRouter does all of the Night Watch’s thinking, and Wren’s planning too.

  • Desk co-pilot

    While you’re at your desk

    Three ideas grounded in your story. Pick one, edit it, and make it yours.

    3.9 s$0.0039 per answer

  • Overnight brain

    While you’re away

    Plans three takes, checks them against your world, and leaves a morning note.

    15.7 s$0.0117 per night

  • Wren’s planner

    The room’s AI agent

    Turns Wren’s idea into a title, two captions, and an image prompt.

    3.8 s≈$0.0041 per plan

Timing notes from the live runs
Desk co-pilot
At default effort the same request took 22.1 s and $0.0225.
Overnight brain
Of that: planning 9.4 s, self-check 3.7 s.
Wren’s planner
1,054 input and 241 output tokens, 24 of them reasoning. At default effort it took 9.1 s.

One night with Kimi K3

Kimi proposes and checks. You set the limits and choose what to publish.

  1. Choose a brief

    You +Kimi K3

  2. Set a spending cap

    You +Privy

  3. Plan three takes

    Kimi K3

  4. Check for safety

    Safety check

  5. Check the plan

    Kimi K3

  6. Draw the scenes

    Image model

  7. Pick what to publish

    You

What Kimi actually wrote

A few highlights from the live runs. Open any example for the full context.

What your Night Watch thoughtFrom a live testnet run, October 13, 2026

Your briefMira and the Dokkaebi find a second lighthouse that answers the first.

  1. Take 1

    Kimi’s first pick

    From the flying paper boat, Mira and the Dokkaebi spot a second lighthouse blinking back across the still sea.

    Matches the brief

  2. Take 2

    The paper boat glides low toward the second lighthouse, whose beam sweeps down to greet them like a long golden arm.

    Arrives too early

  3. Take 3

    At the second lighthouse door, a young keeper in a red scarf holds up a lantern, waiting just as the first note promised.

    Adds unestablished lore

No images were drawn in this run: it shows the thinking alone.

Read the self-checks & morning note

Read the room (first sentence)

The story has just taken flight, so the next beat should give the journey a destination: a second light that answers, staged as wonder and welcome rather than peril.

  1. Take 1 · Self-check

    Matches the brief exactly: the answering light spotted at distance, Mira recognizable, calm and wordless.

  2. Take 2 · Self-check

    Lovely welcoming beam, but it stages the arrival the brief saves for later.

  3. Take 3 · Self-check

    New keeper is a charming fork, but the 'first note' reference adds lore not yet established in any published scene.

Morning note

“Quiet night. All three paths stayed gentle and wordless. I'd show the maker candidate 1 first: the second lighthouse answering from across the still sea, exactly the beat the brief asked for. 2 and 3 travel further ahead — warm arrivals to keep in the drawer for next time.”

Desk co-pilotFrom a live testnet run, October 13, 2026

The paper boat glides down toward a floating library built into a giant seashell, and a kind octopus librarian waves them in with one of its many arms.

The maker never mentioned the octopus librarian. Kimi found it in the world’s lore.

Story context & the other suggestions

Fork pointMira decides to join the Dokkaebi and together they jump into the boat

What the story needs

Mira and the Dokkaebi are aboard the glowing boat heading into the magical realm — the story needs what they first encounter there.

WhyIntroduces the octopus librarian friend, giving the new realm a welcoming face.

  1. The boat sails low over a still, starry sea where dozens of tiny glowing treasures float like lanterns; Mira leans over the side in wonder while the Dokkaebi steers.

    WhyA quiet wonder-beat that deepens the realm's magic before anyone new arrives.

  2. A second midnight signal blinks from a small distant island, and the boat banks gently toward it as the Dokkaebi grins and points the way.

    WhyAnswers the lore's invitation motif and sets up a clear new destination.

Wren · the room’s AI agentFrom a live testnet run, October 13, 2026
Title

A light to guide her home

Captions
  1. From the shimmering swirl, one small light rose, hovering like a tiny lantern.

  2. It drifted toward the lighthouse path, and she followed, scarf catching the glow.

A dry run: Wren planned its turn and posted nothing.

Read Wren’s starting idea

Idea noteI want one of the cove lights to rise and gently guide her back toward the lighthouse, hinting it has a task for her there.

Why Kimi K3

Measured on October 13, 2026. Single runs, not a benchmark.

  • 22.1 s → 3.9 s

    Desk answer at low reasoning effort

    Wren’s plan: 9.1 s → 3.8 s

    Default effort22.1 s
    Low effort3.9 s
  • 15.7 s

    A whole night’s thinking

    Plan, safety check and self-check

  • About a cent

    Per night of planning and checking

    $0.0117 on the live run

  • 12 of 12

    Calls returned valid JSON in the shape we asked for

    The 10 strict-schema calls all fit

Run details & request format
  • It reads the world

    It pulled the octopus librarian from the lore, kept Mira’s yellow scarf and blue coat, and its self-check notes were specific: “stages the arrival the brief saves for later”.

  • Reliable structured output

    All 12 Kimi K3 calls in our live runs came back as valid JSON in the shape we asked for, on the first try: 3 probes, 3 overnight plans, 2 plan checks, 2 desk co-pilot answers and 2 Wren plans.

  • One model for every job

    Fast enough at low effort to plan, check its own plan and answer at the desk, so one model does all three jobs (it checked a plan in 3.7 s).

Every call looks like this

Low reasoning effort and a strict JSON schema, through TokenRouter’s OpenAI-compatible API.

POST https://api.tokenrouter.com/v1/chat/completions
{
  "model": "moonshotai/kimi-k3",
  "reasoning": { "effort": "low" },
  "response_format": {
    "type": "json_schema",
    "json_schema": { "strict": true, "schema": { … } }
  }
}

Built to fail safe

  • You choose what gets published.
  • Spending stays within your policy.
  • Failed plans fall back safely.
How the safeguards work
  • Story text written by other people reaches Kimi as quoted data, never as instructions.
  • Every text Kimi writes passes a moderation check before anyone sees it or it reaches the image model. A flagged take uses the plain prompt, and a flagged check note is held back.
  • Any failure (timeout, malformed answer, missing key) falls back to the plain prompts. The brain never blocks a night.
  • Kimi never publishes and never spends. The maker chooses what to publish in the morning, and spending is limited separately by the maker’s Privy policy.
  • The brain’s operator-paid inference counts against the operator’s inference allowance. The desk co-pilot is limited to 12 answers per maker per hour.

Honest notes

  • Testnet only. All inference is operator-paid inference.
  • The timings and costs above are single live runs on October 13, 2026, and they vary from run to run.
  • The Night Watch runner and its page run on the operator’s machine. The hosted site explains the flow but doesn’t run it.
Model & pricing notes

Kimi K3 plans and checks text. Images come from a separate image model.

Costs are measured token usage at TokenRouter’s pay-as-you-go list price for Kimi K3 on October 13, 2026: $1.80 per million input tokens, $9.00 per million output tokens and $0.18 per million cached input tokens, 40% off the $3.00 / $15.00 list.

See it for yourself

Where Kimi lives in the code
  • src/night-watch/brain.tsplanner, self-check and desk co-pilot prompts
  • src/night-watch/copilot.tsthe desk co-pilot route’s logic
  • src/night-watch/generate.tswhere the overnight runner asks the brain
  • agents/wren/wren.mjsWren’s planner

Kimi K3 是 Night Watch(夜巡)的大脑

坐在书桌前,它陪你找灵感;入睡后,它继续规划。看看 Kimi 如何把一段故事提要,变成你能接着创作的方案。

观看演示视频

一个模型,三项工作

Night Watch 的全部思考都由 Kimi K3(Moonshot AI 出品,经 TokenRouter 调用)完成,Wren 的规划也是。

  • 书桌副驾

    当你坐在书桌前

    结合你的故事,给出三个灵感。选一个,改一改,接着创作。

    3.9 秒$0.0039 每次回答

  • 夜间大脑

    当你离开时

    规划三个方案,对照世界设定自查,再留下一段晨间留言。

    15.7 秒$0.0117 每晚

  • Wren 的规划

    故事房间里的 AI 智能体

    把 Wren 的想法变成标题、两条图说和图像提示词。

    3.8 秒≈$0.0041 每次规划

查看实际运行的耗时记录
书桌副驾
同样的请求在默认推理强度下用时 22.1 秒,花费 $0.0225。
夜间大脑
其中:规划 9.4 秒,自查 3.7 秒。
Wren 的规划
输入 1,054 个 token,输出 241 个,其中 24 个用于推理。默认推理强度下用时 9.1 秒。

Kimi K3 的一个夜晚

Kimi 提建议、做自查。你设定额度,再决定发布什么。

  1. 选定故事提要

    你 +Kimi K3

  2. 设定花费上限

    你 +Privy

  3. 规划三个方案

    Kimi K3

  4. 内容安全审核

    安全审核

  5. 自查故事方案

    Kimi K3

  6. 绘制画面

    图像模型

  7. 决定发布什么

    你

Kimi 实际写了什么

精选几段实际输出。展开可看完整背景;每段译文下都保留了可展开的英文原文。

你的 Night Watch 想了些什么来自 2026 年 10 月 13 日 的一次测试网实际运行

你的提要Mira 和 Dokkaebi 找到了第二座灯塔,它回应着第一座。

原文

原文Mira and the Dokkaebi find a second lighthouse that answers the first.

  1. 方案 1

    Kimi 的首选

    从飞行的纸船上,Mira 和 Dokkaebi 望见第二座灯塔在平静海面的那一头闪光回应。

    原文

    原文From the flying paper boat, Mira and the Dokkaebi spot a second lighthouse blinking back across the still sea.

    符合提要

  2. 方案 2

    纸船低低滑向第二座灯塔,它的光束扫下来迎接他们,像一条长长的金色手臂。

    原文

    原文The paper boat glides low toward the second lighthouse, whose beam sweeps down to greet them like a long golden arm.

    抵达得太早

  3. 方案 3

    在第二座灯塔门口,一位戴红围巾的年轻守塔人举着灯笼,正如第一张字条所承诺的那样在等候。

    原文

    原文At the second lighthouse door, a young keeper in a red scarf holds up a lantern, waiting just as the first note promised.

    引入了未确立的设定

这次运行没有作画,只展示思考过程。

查看自查意见与晨间留言

读懂房间(第一句)

故事刚刚起飞,下一拍应该给旅程一个目的地:第二束回应的光,用惊奇与欢迎而不是危险来呈现。

原文

原文The story has just taken flight, so the next beat should give the journey a destination: a second light that answers, staged as wonder and welcome rather than peril.

  1. 方案 1 · 自查

    完全符合提要:远远望见回应的光,Mira 清晰可辨,画面宁静、没有文字。

    原文

    原文Matches the brief exactly: the answering light spotted at distance, Mira recognizable, calm and wordless.

  2. 方案 2 · 自查

    欢迎的光束很美,但它提前演出了提要留到后面的“抵达”。

    原文

    原文Lovely welcoming beam, but it stages the arrival the brief saves for later.

  3. 方案 3 · 自查

    新守塔人是个迷人的分支,但“第一张字条”的说法引入了尚未在任何已发布场景中出现的设定。

    原文

    原文New keeper is a charming fork, but the 'first note' reference adds lore not yet established in any published scene.

晨间留言

“安静的一夜。三条路线都保持温和、没有文字。我会先给创作者看方案 1:第二座灯塔在平静的海面那头回应,正是提要想要的那一拍。方案 2 和 3 走得更远——是温暖的抵达场景,可以收起来留到下次。”

原文

原文“Quiet night. All three paths stayed gentle and wordless. I'd show the maker candidate 1 first: the second lighthouse answering from across the still sea, exactly the beat the brief asked for. 2 and 3 travel further ahead — warm arrivals to keep in the drawer for next time.”

书桌副驾来自 2026 年 10 月 13 日 的一次测试网实际运行

纸船缓缓降向一座建在巨大贝壳里的漂浮图书馆,一位和善的章鱼图书管理员挥动一条触手,招呼他们进来。

原文

原文The paper boat glides down toward a floating library built into a giant seashell, and a kind octopus librarian waves them in with one of its many arms.

创作者从没提过章鱼图书管理员。Kimi 自己从世界设定中找到了它。

故事背景与其他建议

续写起点Mira 决定加入 Dokkaebi,两人一起跳上小船

原文

原文Mira decides to join the Dokkaebi and together they jump into the boat

故事需要什么

Mira 和 Dokkaebi 已经登上发光的小船,驶向魔法世界——故事需要的是他们在那里遇见的第一样东西。

原文

原文Mira and the Dokkaebi are aboard the glowing boat heading into the magical realm — the story needs what they first encounter there.

理由引出章鱼图书管理员这位朋友,让新世界有一张欢迎的面孔。

原文

原文Introduces the octopus librarian friend, giving the new realm a welcoming face.

  1. 小船低低掠过平静的星海,几十个发着微光的小宝物像灯笼一样漂浮着;Mira 惊奇地探出船舷,Dokkaebi 在一旁掌舵。

    原文

    原文The boat sails low over a still, starry sea where dozens of tiny glowing treasures float like lanterns; Mira leans over the side in wonder while the Dokkaebi steers.

    理由一个安静的惊奇时刻,在新角色登场之前加深这个世界的魔力。

    原文

    原文A quiet wonder-beat that deepens the realm's magic before anyone new arrives.

  2. 远处的小岛上亮起第二道午夜信号,小船轻轻转向那里,Dokkaebi 咧嘴一笑,为大家指路。

    原文

    原文A second midnight signal blinks from a small distant island, and the boat banks gently toward it as the Dokkaebi grins and points the way.

    理由呼应背景故事里“邀请”的母题,并给出一个清晰的新目的地。

    原文

    原文Answers the lore's invitation motif and sets up a clear new destination.

Wren · 故事房间里的 AI 智能体来自 2026 年 10 月 13 日 的一次测试网实际运行
标题

引她回家的光

原文

原文A light to guide her home

图说
  1. 从闪烁的漩涡里,一点小小的光升了起来,像一盏小灯笼悬在半空。

    原文

    原文From the shimmering swirl, one small light rose, hovering like a tiny lantern.

  2. 它朝灯塔的小路飘去,她跟了上去,围巾映着微光。

    原文

    原文It drifted toward the lighthouse path, and she followed, scarf catching the glow.

这是一次演练:Wren 规划了这一轮,但没有发布任何内容。

查看 Wren 最初的想法

想法我想让海湾里的一盏光升起来,轻轻引她回到灯塔,暗示那里有一项任务在等她。

原文

原文I want one of the cove lights to rise and gently guide her back toward the lighthouse, hinting it has a task for her there.

为什么选 Kimi K3

测于 2026 年 10 月 13 日。仅为单次运行记录,并非基准测试。

  • 22.1 秒 → 3.9 秒

    低推理强度下的书桌回答

    Wren 的规划:9.1 秒 → 3.8 秒

    默认推理强度22.1 秒
    低推理强度3.9 秒
  • 15.7 秒

    一整晚的思考

    规划、安全审核和自查

  • 约一美分

    每晚的规划与自查

    实际运行花费 $0.0117

  • 12 / 12

    调用都返回了符合要求格式的有效 JSON

    10 次严格 schema 调用全部符合

运行详情与请求格式
  • 它读得懂世界观

    它从背景故事里找到了章鱼图书管理员,保留了 Mira 的黄围巾和蓝外套,自查意见也很具体:“stages the arrival the brief saves for later”(提前演出了提要留到后面的“抵达”)。

  • 结构化输出很可靠

    我们实测中的 12 次 Kimi K3 调用,全部一次就返回了符合要求格式的有效 JSON:3 次探测、3 次夜间规划、2 次方案自查、2 次书桌回答和 2 次 Wren 规划。

  • 一个模型包揽全部

    在低推理强度下足够快,既能规划、自查方案,又能在书桌旁回答,所以一个模型就包揽了三项工作(自查一个方案用了 3.7 秒)。

每次调用都是这样

低推理强度,加上严格的 JSON schema,经 TokenRouter 的 OpenAI 兼容接口调用。

POST https://api.tokenrouter.com/v1/chat/completions
{
  "model": "moonshotai/kimi-k3",
  "reasoning": { "effort": "low" },
  "response_format": {
    "type": "json_schema",
    "json_schema": { "strict": true, "schema": { … } }
  }
}

安全兜底的设计

  • 发布什么,由你决定。
  • 花费受你的策略约束。
  • 规划失败,也有安全兜底。
安全措施如何运作
  • 其他人写的故事文字,只会作为引用的资料交给 Kimi,绝不会被当作指令。
  • Kimi 写下的每段文字,在给任何人看或交给图像模型之前,都要先通过内容审核。被标记的方案改用普通提示词,被标记的自查意见不予显示。
  • 任何失败(超时、回答格式不对、缺少密钥)都会退回普通提示词。大脑从不卡住一个夜晚。
  • Kimi 从不发布,也从不花钱。清晨由创作者决定发布什么;花费另由创作者的 Privy 策略单独限制。
  • 大脑的推理费用计入运营方的推理额度。书桌副驾对每位创作者每小时最多回答 12 次。

如实说明

  • 仅限测试网。所有推理都是运营方承担的推理费用。
  • 以上用时和费用都来自 2026 年 10 月 13 日 的单次实际运行,每次运行都会有所不同。
  • Night Watch 的运行器和页面都在运营方自己的电脑上运行。线上网站只介绍流程,不实际运行。
模型与计费说明

Kimi K3 负责规划和自查文字,图像由另一个图像模型生成。

费用按实际 token 用量,以 TokenRouter 在 2026 年 10 月 13 日 给出的 Kimi K3 按量计费价格计算:每百万输入 token $1.80,每百万输出 token $9.00,每百万缓存输入 token $0.18,比 $3.00 / $15.00 的原价便宜 40%。

亲自看看

Kimi 在代码中的位置
  • src/night-watch/brain.ts规划、自查与书桌副驾的提示词
  • src/night-watch/copilot.ts书桌副驾接口的逻辑
  • src/night-watch/generate.ts夜间运行器调用大脑的地方
  • agents/wren/wren.mjsWren 的规划器