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Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
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FR-AI / ANALYSISWhy it is worth attention
It directly addresses the main bottleneck in AI-assisted coding — undefined unknowns — by making Claude an active partner in surfacing them before they become expensive errors.
Who it is for
- Developers using Claude Code
- Project leads managing complex AI-assisted tasks
- AI coding enthusiasts interested in prompt engineering
- Anyone who wants to reduce guesswork in AI interactions
Use cases
- Pre-implementation blindspot discovery and brainstorming
- Creating implementation plans that surface hidden assumptions
- Post-implementation verification via explainer and quiz
- Reducing silent deviations in long-horizon coding tasks
Strengths
- Based on proven methodology from Anthropic's field guide
- Easy to install as global or per-project rules
- Provides concrete techniques for each stage of development
- Explicitly balances discovery vs. speed for trivial tasks
Considerations
- Bias toward discovery may slow down very simple tasks
- Requires Claude Code as the AI tool
- Effectiveness depends on the user's ability to engage with the prompted discoveries
README quick start
Finding-Your-Unknowns Claude Code Guidelines
Maintained by 泊舟 Bozhou — I write about AI and agentic coding on X, follow me at x.com/bozhou_ai.
English | 简体中文
A single CLAUDE.md file that turns Thariq's (Anthropic) field guide — A Field Guide to Fable: Finding Your Unknowns — into behavioral guidelines for Claude Code.
The Problem
From Thariq's article:
Working with Claude Fable 5 keeps re-teaching me an old lesson: the map is not the territory.
The difference between the map and the territory is what I call unknowns. When Claude runs into an unknown, it needs to make a decision based on its best guess of what I want.
Fable is the first model where I find the quality of the work is bottlenecked by my ability to clarify its unknowns.
Your prompt is a map. The codebase is the territory. Everything you didn't say — and everything you didn't know to say — is an unknown, and every unknown forces Claude to guess. Accumulated wrong guesses are how long tasks go badly off course.
The Solution
Make Claude an active partner in discovering your unknowns, at every stage:
| Technique | Stage | Uncovers |
|---|---|---|
| Blindspot Pass | Pre-implementation | Unknown unknowns |
| Brainstorm & Prototype | Pre-implementation | Unknown knowns |
| Interview | Pre-implementation | Known unknowns |
| References | Pre-implementation | What you can't put into words |
| Implementation Plan | Pre-implementation | Decisions you'll want to tweak |
| Implementation Notes | During implementation | Deviations from the plan |
| Explainer & Quiz | Post-implementation | What actually changed |
The Four Kinds of Unknowns
- Known knowns — what's in your prompt.
- Known unknowns — what you know you haven't figured out yet.
- Unknown knowns — what's so obvious you'd never write it down, but you'd recognize it if you saw it.
- Unknown unknowns — what you haven't considered at all.
The guidelines instruct Claude to surface the last three instead of silently guessing through them.
Install
Global rules (recommended) — applies to every Claude Code session:
echo "" >> ~/.claude/CLAUDE.md
curl https://raw.githubusercontent.com/bozhouDev/finding-unknowns-skills/main/CLAUDE.md >> ~/.claude/CLAUDE.md
**Per-p
Description
Unknown-discovery guidelines for Claude Code, derived from Thariq's (Anthropic) 'A Field Guide to Fable: Finding Your Unknowns'
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