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Agent Skill · 研究检索

learning-log(学习日志)

learning-log 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

learning-log 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 54,843。

总安装 494周安装 20GitHub Stars 315下载 155核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:learning-log(学习日志)
来源仓库:https://github.com/codewithmukesh/dotnet-claude-kit
仓库路径:skills/learning-log
安装命令:
npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill learning-log
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill learning-log

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于记录 Agent 执行过程与用户交互细节,形成学习闭环。适合在调试、复盘或持续优化任务中使用。learning-log 属于研究检索类 Skill,可作为该场景下的辅助能力补充。通过 .NET 项目仓库安装,兼容 Codex、Claude 等平台。日志格式应包含时间戳、动作类型与结果状态。

需控制日志粒度,避免影响性能或泄露隐私。

来源仓库内路径:skills/learning-log

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill learn…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

learning-log 怎么安装?

在终端执行 npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill learning-log。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

learning-log 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

learning-log 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

learning-log 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

learning-log 用的人多吗?

公开数据是累计安装 494 次,近一周安装 20 次,下载 155 次,GitHub 315 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

learning-log 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
learning-log

学习日志 · 本页

494315调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Learning Log

Core Principles

  1. Log insights, not rules — MEMORY.md stores corrective rules ("always use X instead of Y"). The learning log stores discoveries ("X behaves differently when Y is configured because Z"). Rules prescribe behavior; insights explain the world.
  2. Structure enables searchability — Every entry has a date, category, title, description, and affected files. Consistent structure means you can search by category, scan titles, or find entries related to specific files.
  3. Log during work, not after — Capture insights the moment they occur. Waiting until the end of a session means half the detail is lost. A 2-line entry written immediately is worth more than a paragraph reconstructed from memory.
  4. Periodic review extracts patterns — A monthly scan of the learning log reveals recurring themes. Three "gotcha" entries about the same subsystem suggests a systemic issue worth addressing. Individual entries are useful; patterns across entries are actionable.
  5. Distinct from handoff notes — The wrap-up-ritual handoff captures session state (done/pending/learned). The learning log is a persistent, growing knowledge base. Handoffs are overwritten; the log only grows (and is periodically pruned).

Patterns

Log Entry Format

Each entry follows a consistent structure in .claude/learning-log.md:

# Learning Log

## 2025-07-15 | Bug Root Cause | EF Core SaveChanges Silently Succeeds on Duplicate Keys
`SaveChangesAsync` with a duplicate PK throws on the *next* `SaveChangesAsync` call, not the insert.
**Files:** `src/Orders/Features/CreateOrder.cs:42`
**Resolution:** Call `SaveChangesAsync` immediately after `Add()`, before any other operations.

## 2025-07-12 | Gotcha | MassTransit Consumer Registration Order Matters
Multiple consumers for the same message type run in registration order. If the first throws,
subsequent consumers are skipped. Caused missed audit events.
**Files:** `src/Shared/Extensions/MassTransitConfig.cs:15-30`
**Resolution:** Configure independent consumer endpoints or use the retry filter.

Auto-Logging Triggers

Log entries automatically when these situations occur:

TRIGGER 1: Non-Obvious Bug Root Cause
When debugging reveals the root cause is NOT where the error appeared.
→ Log the misdirection, the actual cause, and how to avoid confusion.

TRIGGER 2: Undocumented Architecture Decision
When you discover WHY something was built a certain way (not just HOW).
→ Log the decision, the alternatives considered, and the rationale.

TRIGGER 3: Workaround for Framework/Library Limitation
When the "correct" approach doesn't work and you need an alternative.
→ Log what didn't work, why, and what works instead.

TRIGGER 4: Performance Finding
When profiling or observation reveals unexpected performance behavior.
→ Log the finding, the measurement, and the optimization applied.

TRIGGER 5: External Service Behavior
When an external API/service behaves differently than documented.
→ Log the expected vs actual behavior and any workaround.

TRIGGER 6: Non-Obvious Configuration
When a setting or configuration has a surprising effect.
→ Log the configuration, the surprising behavior, and the correct setup.

Category System

Use these 6 categories consistently:

Architecture Decision  — WHY something is structured a certain way
Bug Root Cause        — Non-obvious bugs where the error ≠ the cause
Performance Discovery — Unexpected performance behavior or optimization
Pattern Found         — Reusable pattern discovered in the codebase
Gotcha                — Surprising behavior in frameworks, libraries, or APIs
External Service      — Quirks of third-party services and APIs

Practical Logging Workflow

How to log during active development:

DURING WORK:
1. You encounter something non-obvious
2. Spend 30 seconds writing a log entry (2-4 lines)
3. Include the category, a descriptive title, and affected files
4. Continue working — the entry is captured, detail can be added later

ENTRY QUALITY LEVELS:
Quick (during work):  Date | Category | Title + 1-line description + files
Full (if time allows): Date | Category | Title + full description + resolution + files

A quick entry is infinitely better than no entry.

Log vs. Memory vs. Handoff

Distinguish between the three knowledge stores:

MEMORY.md (via self-correction-loop):
- Contains: Prescriptive rules ("always do X", "never do Y")
- Source: User corrections, promoted learning log entries
- Lifespan: Permanent until proven wrong
- Format: Category → bullet point rules

.claude/learning-log.md (this skill):
- Contains: Descriptive insights ("X happens because Y")
- Source: Organic discoveries during development
- Lifespan: 3-6 months, then archive or promote
- Format: Date | Category | Title | Description | Files

.claude/handoff.md (via wrap-up-ritual):
- Contains: Session state (done/pending/learned)
- Source: End of each session
- Lifespan: Until next session overwrites it
- Format: Completed / Pending / Learned sections

Anti-patterns

Logging Everything

// BAD — low-value entries that add noise
## 2025-07-15 | Pattern Found | Used Primary Constructors
Used primary constructors for the OrderService class.
**Files:** src/Orders/OrderService.cs

// GOOD — only log when it's non-obvious or surprising
## 2025-07-15 | Gotcha | Primary Constructor Parameters Captured as Fields
Primary constructor parameters in C# 14 are implicitly captured as fields.
If you also declare an explicit field with the same name, you get a compiler
warning but no error — and the two can silently diverge.
**Files:** src/Orders/OrderService.cs:5

No Categorization

// BAD — entries without categories are unsearchable
## 2025-07-15 | Compiled queries don't support Include()
## 2025-07-14 | MassTransit consumer ordering matters
## 2025-07-13 | Orders module uses VSA, Identity uses CA

// GOOD — categories enable filtering and pattern detection
## 2025-07-15 | Performance Discovery | Compiled Queries Don't Support Include()
## 2025-07-14 | Gotcha | MassTransit Consumer Registration Order Matters
## 2025-07-13 | Architecture Decision | Why Orders Uses VSA While Identity Uses CA

Write-Only Log (Never Reviewed)

// BAD — 100 entries, never reviewed
.claude/learning-log.md grows to 500 lines
Same gotchas keep appearing because no one reads the log
No entries are promoted to MEMORY.md

// GOOD — monthly reviews extract value
Every 20 entries, scan for patterns
Promote recurring findings to MEMORY.md as preventive rules
Archive stale entries
The log stays lean and the rules get stronger

Duplicating MEMORY.md Content

// BAD — restating a MEMORY.md rule as a log entry
MEMORY.md: "Always use TimeProvider instead of DateTime.Now"
learning-log.md: "## Gotcha | DateTime.Now Is Not Testable" ← redundant

// GOOD — log adds a concrete incident the rule doesn't capture
learning-log.md: "## Bug Root Cause | Flaky Test Due to DateTime.Now
  OrderExpiry test failed intermittently — DateTime.Now crossed midnight during run."

Decision Guide

ScenarioAction
Found a non-obvious bug root causeLog it — category: Bug Root Cause
Discovered why code is structured a certain wayLog it — category: Architecture Decision
Framework behaved unexpectedlyLog it — category: Gotcha
Performance surprise (good or bad)Log it — category: Performance Discovery
Found a reusable pattern in the codebaseLog it — category: Pattern Found
External API behaved differently than docs sayLog it — category: External Service
User corrected Claude's codeDon't log — use self-correction-loop for MEMORY.md
Routine code change, nothing surprisingDon't log — only log insights
Same gotcha appeared 3+ times in the logPromote to MEMORY.md as a preventive rule
Learning log exceeds 50 entriesMonthly review — archive old, promote recurring
Starting a new sessionScan recent log entries for context on the working area

平台分布

Codex

33.95%
按下载量换算53

Claude

34.05%
按下载量换算53

Cursor

17.6%
按下载量换算27

Gemini CLI

9.31%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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