Borrowing it
Nothing to install: this file belongs to huifer/claude-code-interview. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/huifer/claude-code-interview/main/.claude/commands/weakness/plan.mdgit clone --depth 1 https://github.com/huifer/claude-code-interviewWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/huifer/claude-code-interview/plan)<a href="https://agentmods.dev/commands/huifer/claude-code-interview/plan"><img src="https://agentmods.dev/badge/commands/huifer/claude-code-interview/plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/huifer/claude-code-interview/plan"><img src="https://agentmods.dev/badge/commands/huifer/claude-code-interview/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.03773 |
| Opus 5.5 | $0.00012 | $0.01509 |
| Sonnet 5.5 | $0.00006 | $0.00755 |
| Haiku 4.5 | $0.00003 | $0.00377 |
Grade A, and why
plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 586 lines — stays where its author put it; the contents beside it link to each section on GitHub.
生成弱点改进计划
分析面试表现和技能差距,生成系统化的改进计划。
使用方法
基于最近面试生成计划
/weakness/plan
# 将使用最近一次面试的数据
基于特定面试生成计划
/weakness/plan google-round1
# 使用特定面试的反馈数据
聚焦特定领域
/weakness/plan --technical
# 只关注技术弱点
/weakness/plan --behavioral
# 只关注行为面试弱点
/weakness/plan --communication
# 只关注沟通弱点
分析维度
1. 技术弱点分析
基于面试反馈分析:
算法和数据结构
{
"weakness": {
"category": "Algorithms",
"issues": [
{
"problem": "DP问题优化思路不清晰",
"frequency": "出现3次",
"severity": "major",
"impact": "未能通过 coding round"
}
],
"root_cause": "缺乏系统练习,DP模式掌握不足",
"improvement_plan": {
"resources": [
"LeetCode DP专题 - 50题",
"《算法导论》动态规划章节",
"TechLead DP模式视频"
],
"practice_plan": [
"Week 1-2: 基础DP模式 (Fibonacci, Climbing Stairs)",
"Week 3-4: 背包问题系列",
"Week 5-6: LCS, LIS系列",
"Week 7-8: 综合问题"
],
"success_criteria": "连续10道DP题 >80%正确率"
}
}
}
系统设计
{
"weakness": {
"category": "System Design",
"issues": [
{
"problem": "Scalability考虑不足",
"examples": ["未考虑数据分片", "缺少缓存策略"],
"severity": "critical",
"improvement_needed": "深入学习大规模系统设计"
}
],
"resources": [
"DDIA - Designing Data-Intensive Applications",
"System Design Primer",
"Google SRE书籍"
]
}
}
2. 沟通弱点分析
清晰度
{
"communication": {
"clarity": {
"current_level": "中等",
"issues": [
"解释问题时思路跳跃",
"缺少结构化表达",
"术语使用不一致"
],
"improvement_plan": {
"techniques": [
"使用STAR方法组织答案",
"先给出概述再深入细节",
"使用First, Next, Finally结构"
],
"practice": [
"每天口头解释一个算法问题",
"录制自己的回答并回听",
"与练习伙伴mock interview"
],
"timeline": "2-3周可见改善"
}
}
}
}
主动沟通
{
"communication": {
"proactive": {
"issues": [
"等待interviewer提示",
"不主动clarify需求",
"缺少中间checkpoints"
],
"best_practices": [
"开始前确认问题理解",
"每5分钟口头说明思路",
"遇到歧义立即提问",
"主动讨论trade-offs"
]
}
}
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 586 lines · 0 tokens per session scan A bc8671f9028b
plan is a command published in the GitHub repository huifer/claude-code-interview (27 stars, last pushed 10mo ago), licensed MIT. It adds 30 tokens to every session and 3,773 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
plan compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| planhuifer/claude-code-interview | Command | 27 | 10mo ago | MIT | A | 30 | Claude Code |
| learn-story-flowIntai/story-flow | Command | 16 | 2d ago | MIT | A | 10 | Claude Code |
| start-10-1minicoohei/ai-agent-camp | Command | 347 | 1mo ago | none | A | 2 | Claude Code |
| start-0-8minicoohei/ai-agent-camp | Command | 347 | 1mo ago | none | A | 2 | Claude Code |
| setup-m365cli.esminicoohei/ai-agent-camp | Command | 347 | 1mo ago | none | A | 8 | Claude Code |
| prep-rolefourleafai/clover-public | Command | 8 | 1mo ago | MIT | A | 0 | Claude Code |
| setup-vercel.esminicoohei/ai-agent-camp | Command | 347 | 1mo ago | none | B | 2 | Claude Code |