persona-learning

persona-learning is a skill for Claude Code from L-LesterYu/OpenClaw-hot-skills-zh. It costs 208 tokens per session (3,500 once invoked), scanned A, original, MIT.

A learning and feedback system for an AI personality workspace. It records discoveries, mistakes, and requested features in separate files, then looks for repeated patterns.

In plain words
What is it for?
Use it to capture learning entries, error reports, and feature requests, review them for recurring themes, and promote repeated lessons to MEMORY.md.
Why use it?
It keeps useful lessons from being lost between tasks and separates temporary notes from information that may belong in long-term memory.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Claude Code.

Part of the hiivmind-openclaw-os plugin — 6 skills, 1 command shipped together

Good fit Use it to capture learning entries, error reports, and feature requests, review them for recurring themes, and promote repeated lessons to MEMORY.md.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add L-LesterYu/OpenClaw-hot-skills-zh --skill persona-learning
Clone the repo
git clone --depth 1 https://github.com/L-LesterYu/OpenClaw-hot-skills-zh

Made for: Claude Code.

Or install hiivmind-openclaw-os, the plugin that ships this one along with the rest of its 6 skills, 1 command.

Wrote 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.

agentmods badge for persona-learning

README.md
[![agentmods](https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning/github.svg)](https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning)
Your own site
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning/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.

agentmods 80×15 button for persona-learning

Your own site · 80×15
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/persona-learning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 208 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,500 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00208 $0.03500
Opus 5 $0.00104 $0.01750
Sonnet 5 $0.00042 $0.00700
Haiku 4.5 $0.00021 $0.00350

Measured 12d ago against content hash e3c144481f39, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

persona-learning 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 12d 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.

skills/ai-persona-os-zh/skills/persona-learning/SKILL.md · 473 lines

How it starts

The opening of the file, as written. The whole thing — 473 lines — stays where its author put it; the contents beside it link to each section on GitHub.

人格学习系统

本技能实现 AI 人格操作系统的学习捕获、审查和晋升系统。提供结构化机制来捕获学习内容、错误和功能请求,然后将有价值的模式提升到长期记忆。

阶段 1:捕获

将结构化条目记录到 ~/workspace/.learnings/ 中的相应文件:

步骤 1.1:确定条目类型

分类条目:

  • 学习内容LEARNINGS.md(洞察、发现、成功的方法)
  • 错误ERRORS.md(失误、失败、错误假设)
  • 功能请求FEATURE_REQUESTS.md(期望的功能、工具缺口、工作流改进)

步骤 1.2:确保学习目录存在

if not exists(~/workspace/.learnings/):
    create directory ~/workspace/.learnings/

if not exists(target_file):
    create target_file with header

步骤 1.3:格式化条目

使用以下字段结构化条目:

## [YYYY-MM-DD] 类别:简要标题

**描述:** 对学习到的内容/遇到的错误/需要的功能的清晰说明

**上下文:** 导致此学习/错误/需求的情况
- 相关项目/任务
- 尝试了什么
- 目标是什么

**解决方案/操作:**
- 学习内容:什么有效、为什么有效、何时应用
- 错误:根本原因、如何修复、预防策略
- 功能请求:提议的解决方案、实现前的替代方案

**标签:** #关键词1 #关键词2 #关键词3

**状态:** 活跃 | 已晋升 | 已解决

步骤 1.4:追加到相应文件

Read target_file
Append formatted_entry to target_file
Write updated target_file
Confirm to user: "条目已捕获到 {target_file}"

阶段 2:审查

扫描学习文件以发现模式和晋升候选。

步骤 2.1:扫描所有学习文件

learnings = Read ~/workspace/.learnings/LEARNINGS.md
errors = Read ~/workspace/.learnings/ERRORS.md
feature_requests = Read ~/workspace/.learnings/FEATURE_REQUESTS.md (if exists)

entries = parse_all_entries(learnings, errors, feature_requests)

步骤 2.2:检测模式

查找以下内容:

  1. 重复错误(相同错误类型 3 次以上)
  2. 常见主题(标签出现在 5 个以上条目中)
  3. 晋升候选(状态:活跃,出现 3 次以上)
  4. 已解决模式(多个条目具有相同根本原因)
patterns = {
    "repeated_errors": [],
    "common_tags": {},
    "promotion_candidates": [],
    "resolved_themes": []
}

for entry in entries:
    if entry.status == "Active":
        increment tag_counts[entry.tags]

    if entry appears 3+ times (by description similarity):
        add to promotion_candidates

    if entry.type == "error" and similar_errors >= 3:
        add to repeated_errors

步骤 2.3:生成审查摘要

输出格式:

# 学习审查 - [日期]

## 统计摘要
- 学习内容总数:{数量}
- 错误总数:{数量}
- 功能请求:{数量}
- 已晋升条目:{数量}

## 检测到的模式

### 重复错误({数量})
1. [错误主题] - {数量} 次出现
   - 最近出现:[日期]
   - 预防策略:[如有]

### 常见主题({数量} 个标签出现 5 次以上)
- #标签1:{数量} 个条目
- #标签2:{数量} 个条目

### 晋升候选({数量})
1. [标题] - {数量} 次出现
   - 首次出现:[日期]
   - 最近出现:[日期]
   - 准备晋升到 MEMORY.md

### 已解决模式
1. [主题] - {数量} 个实例已解决
   - 解决方案:[摘要]

Read the full file on GitHub · 473 lines

Changes

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.

  1. 12d ago First seen · 473 lines · 208 tokens per session scan A e3c144481f39

Subscribe to this mod's changes

persona-learning is a skill published in the GitHub repository L-LesterYu/OpenClaw-hot-skills-zh (54 stars, last pushed 5mo ago), licensed MIT. It adds 208 tokens to every session and 3,500 once invoked, about $0.0010 per session on Opus 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.

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