Iván

Kimi

AI 智慧體v1.0.0
作者:Iván更新於 2026-05-11kimi@clawhub_ivangdavila/kimi
工作流編排工具呼叫#Coding#Debug

據 AlphaMoat 統計,截至 2026-09,Kimi 累計下載 1,881 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 4,513 位,在「AI 智慧體」分類(969 個)中排名第 892 位。

累計安裝
218
累計下載
1881
星標
-
全站排名
#4,513
全站前 89% · 「AI 智慧體」前 93%
平台累計安裝累計下載星標評論
ClawHub ↗341234--
SkillHub ↗2181881-—

各平台的計數口徑不同,統計時間不一致。

這個技能是做什麼的

透過官方 Moonshot API 核對鑑權與即時模型列表,再按工作負載整理請求、重試、解析及相容介面遷移。結構化輸出須經過驗證或額外規範化後用於下游;傳送敏感資料前需脫敏並取得明確同意。預設無狀態,使用者同意持續使用後才儲存本機筆記或日誌。

資料釋出於 2026-10-26

可以用來做什麼

  • 排查 Kimi 請求或遷移現有用戶端

什麼時候用

  • 鑑權、模型名稱、輸出解析或遷移出現問題時

示例提示詞

以下是根據技能文件生成的示例,不代表實際執行結果。

檢查這段 Kimi 請求的端點、模型選擇和解析邏輯

使用條件

依據技能文件中的宣告整理,未經實際安裝或執行驗證。

鑑權說明
使用環境變數 MOONSHOT_API_KEY,不把值寫入筆記。
配置要求
  • 最小介面檢查需要 curl 與 jq。

月度資料趨勢

累計下載1881
297114819982026-03 · 累計下載 4142026-05 · 累計下載 8402026-06 · 累計下載 9362026-07 · 累計下載 11592026-08 · 累計下載 14152026-09 · 累計下載 188126-0326-09
星標-
0112026-03 · 星標 -2026-05 · 星標 -2026-06 · 星標 -2026-07 · 星標 -2026-08 · 星標 -2026-09 · 星標 -26-0326-09

2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。

月份累計下載環比星標
2026-091881—-
2026-081415+22.1%-
2026-071159+23.8%-
2026-06936+11.4%-
2026-05840—-
2026-03414—-

SKILL.md 原文

以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。

6.6 KB · ClawHub v1.0.0
---
name: Kimi
slug: kimi
version: 1.0.0
homepage: https://clawic.com/skills/kimi
description: Build and debug Kimi API workflows for chat, coding, reasoning, and tool-calling with live model checks, retries, and safe routing.
changelog: Initial release with Kimi workflow routing, OpenAI-compatible request patterns, migration guidance, and operational safety checks.
metadata: {"clawdbot":{"emoji":"🌙","requires":{"bins":["curl","jq"],"env":["MOONSHOT_API_KEY"]},"os":["linux","darwin","win32"],"configPaths":["~/kimi/"]}}
---
展開全部(共 145 行)
## When to Use

User needs Kimi to work reliably for chat, coding, long-context research, structured outputs, or agent workflows. Agent handles live model verification, request shaping, migration from other OpenAI-compatible providers, and failure recovery before the workflow is trusted.

## Architecture

Memory lives in `~/kimi/`. If `~/kimi/` does not exist, run `setup.md`. See `memory-template.md` for structure.

```text
~/kimi/
├── memory.md         # Status, activation rules, and stable defaults
├── routes.md         # Preferred route per workload
├── approvals.md      # Sensitive-send boundaries and redaction preferences
├── experiments.md    # Prompt, parser, and fallback notes
└── logs/             # Optional sanitized repro payloads
```

## Quick Reference

Use the smallest file that resolves the blocker.

| Topic | File |
|-------|------|
| Setup process | `setup.md` |
| Memory template | `memory-template.md` |
| Minimal request patterns | `api-patterns.md` |
| Workload routing choices | `routing-matrix.md` |
| OpenAI-compatible migration | `migration-playbook.md` |
| Trust and redaction workflows | `safety-workflows.md` |
| Fast diagnosis and recovery | `troubleshooting.md` |

## Requirements

- `curl` and `jq` for minimal endpoint checks
- `MOONSHOT_API_KEY` kept in environment variables only
- Kimi access through the official Moonshot API base URL
- User approval before persisting local notes or sanitized logs

## Core Rules

### 1. Verify Auth and Live Models Before Naming Any Route
- Start with `https://api.moonshot.ai/v1/models` and copy live model IDs from the response.
- Never trust remembered Kimi model names, screenshots, or stale blog examples when a workflow is failing now.

### 2. Lock the Job to One Workload Before Tuning Prompts
- Classify the request as one of: fast chat, coding agent, long-context research, deterministic JSON, or migration debugging.
- Most bad Kimi advice comes from mixing several jobs into one oversized prompt and then blaming the model.

### 3. Treat Structured Output as a Separate Reliability Path
- If output feeds tools, code execution, or downstream writes, use strict schemas or a second normalization pass.
- Do not ask one response to do open-ended reasoning and perfect machine-readable output at the same time.

### 4. Keep Sensitive Data Out Unless the User Explicitly Approves It
- Redact secrets, customer identifiers, internal hostnames, and raw tokens before sending prompts externally.
- If the user wants repeatable Kimi workflows, save the redaction rule and approval boundary in `~/kimi/approvals.md` after confirming the first write.

### 5. Route by Deadline and Cost, Not Brand Habit
- Use the smallest Kimi route that can finish the current job reliably.
- For recurring workflows, save one primary route and one fallback route instead of debating models from scratch each time.

### 6. Separate Provider Migration Problems From Model Problems
- When moving from OpenAI-compatible code to Kimi, isolate the variable: base URL, auth env var, model ID, parser, or retry policy.
- Reproduce with one minimal payload before changing prompts, infrastructure, and business logic together.

### 7. Ask Before Creating Persistent State
- Work statelessly by default.
- Only create `~/kimi/` notes, approvals, or debug logs after the user wants continuity across Kimi tasks.

## Common Traps

- Hardcoding a remembered model ID -> fetch `/models` and use the live ID instead.
- Treating Kimi as one generic route -> split coding, reasoning, JSON, and migration work.
- Sending raw internal logs to the API -> redact first and preview what leaves the machine.
- Combining creative reasoning with strict JSON output -> use a second deterministic pass.
- Blaming the model for every failure -> verify auth, base URL, retries, and parser behavior first.

## External Endpoints

Use only the official Moonshot API surface required for the current task.

| Endpoint | Data Sent | Purpose |
|----------|-----------|---------|
| https://api.moonshot.ai/v1/models | Auth header only | Discover live Kimi models |
| https://api.moonshot.ai/v1/chat/completions | Prompt messages and options | Kimi chat, reasoning, coding, and structured-output requests |

No other data is sent externally.

## Security & Privacy

**Data that leaves your machine:**
- Prompt content sent to the Moonshot API when the user asks for Kimi inference
- Optional sanitized excerpts of code, logs, or documents sent for analysis after approval

**Data that stays local:**
- Activation preferences, route defaults, and approval boundaries in `~/kimi/` after user approval
- Optional sanitized repro payloads and troubleshooting notes saved for recurring workflows

**This skill does NOT:**
- Store `MOONSHOT_API_KEY` in markdown or project files
- Send data to undeclared endpoints
- Persist raw secrets or sensitive prompts without explicit user approval
- Modify its own skill files

## Scope

This skill ONLY:
- designs and debugs Kimi API workflows
- routes Kimi usage across coding, reasoning, research, and deterministic-output jobs
- hardens retries, validation, and migration from other OpenAI-compatible providers
- stores lightweight local notes only after user approval

This skill NEVER:
- invent live model availability without checking
- persist secrets in `~/kimi/`
- execute destructive downstream automation from unvalidated output
- treat cost-sensitive or sensitive-send boundaries as implicit

## Trust

Using this skill sends prompt data to Moonshot's Kimi API.
Only install if you trust Moonshot with that data, or keep sensitive preprocessing local and sanitized.

## Related Skills
Install with `clawhub install <slug>` if user confirms:
- `api` — debug auth, payloads, retries, and OpenAI-compatible request shapes
- `models` — compare model families and cost tiers before locking Kimi into production
- `coding` — tighten coding-agent behavior after the Kimi route itself is stable
- `backend` — connect Kimi workflows to services, jobs, and API boundaries
- `fastapi` — expose Kimi-backed endpoints with request validation and safer deployment defaults

## Feedback

- If useful: `clawhub star kimi`
- Stay updated: `clawhub sync`

「AI 智慧體」分類下的熱門技能

self-improving agentAI 智慧體

記錄自身發現以實現自我改進的技能

↓ 129萬★ 4521pskoett
Find SkillsAI 智慧體

幫助使用者發現和安裝智慧體技能,當用戶詢問如「如何做X」、「找X的技能」、「有能做...的嗎」等問題時

↓ 110.3萬★ 1778桂皮
Agent BrowserAI 智慧體

給 AI agent 用的瀏覽器自動化命令列技能。

↓ 90.9萬★ 991Nicolas Kleiber
Self-Improving + Proactive AgentAI 智慧體

自我反思+自我批評+自我學習+自組織記憶。智慧體評估自身工作、發現錯誤並持續改進。

↓ 44.4萬★ 1606Iván
Skill VetterAI 智慧體

在安裝第三方技能之前,按清單審查來源、許可權與危險模式的技能。

↓ 33萬★ 1323spclaudehome
ontologyAI 智慧體

類型化知識圖譜,用於結構化智慧體記憶與可組合技能。適用於以下場景:建立/查詢實體(人物、專案、任務、事件、文件)、關聯相關物件、強制執行約束、將多步操作規劃為圖譜變換,或當技能需要共享狀態時。觸發關鍵詞包括"記住""我知道關於什麼""將X連結到Y""顯示依賴關係"、實體增刪改查操作,以及跨技能資料訪問。

↓ 29.4萬★ 788oswalpalash
Proactive AgentAI 智慧體

將 AI 代理從任務執行者轉變為能夠預見需求、持續最佳化的主動夥伴。現已支援 WAL Protocol、Working Buffer、Autonomous Crons 及經過實戰驗證的模式。屬於 Hal Stack 🦞。

↓ 28.8萬★ 913halthelobster
Skill CreatorAI 智慧體

建立有效技能指南。當用戶希望建立新技能(或更新現有技能)以利用專業知識、工作流程或工具整合擴充套件 Claude 的能力時,應使用此技能。

↓ 23.8萬★ 473chindden

Iván 的其他技能

資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。