Kimi
Build and debug Kimi API workflows for chat, coding, reasoning, and tool-calling with live model checks, retries, and safe routing.
Description
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/"]}}
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.
~/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
curlandjqfor minimal endpoint checksMOONSHOT_API_KEYkept 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/modelsand 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.mdafter 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
/modelsand 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_KEYin 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 shapesmodels— compare model families and cost tiers before locking Kimi into productioncoding— tighten coding-agent behavior after the Kimi route itself is stablebackend— connect Kimi workflows to services, jobs, and API boundariesfastapi— expose Kimi-backed endpoints with request validation and safer deployment defaults
Feedback
- If useful:
clawhub star kimi - Stay updated:
clawhub sync
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