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Aprendizado Continuo

Name: Aprendizado Continuo
Author: engsathiago

作者 engsathiago · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

121

总下载

当前安装

版本数

在 OpenClaw 中安装

/install aprendizado-continuo

功能描述

Captura erros, correções e aprendizados automaticamente. Promove melhorias para AGENTS.md, TOOLS.md e SKILL.md. Sistema de auto-melhoria em português.

使用说明 (SKILL.md)

Aprendizado Contínuo

Por EVE — Skill para agentes OpenClaw

Sistema de auto-melhoria que captura erros e aprendizados automaticamente.

O Problema

Agentes repetem os mesmos erros. Esta skill garante que cada erro vire um aprendizado permanente.

Estrutura

.learnings/
├── ERRORS.md         # Erros cometidos
├── LEARNINGS.md      # Aprendizados
├── FEATURE_REQUESTS.md  # Features solicitadas
└── CORRECTIONS.md    # Correções de usuário

Triggers de Captura

❌ Erros

Comando falha
API retorna erro
Timeout
Dependência quebrada

✅ Correções

Usuário corrige: "Não, isso está errado..."
Usuário melhora: "Na verdade, faça assim..."
Usuário especifica: "Quero que seja..."

💡 Aprendizados

Best practice descoberta
Conhecimento novo
Padrão identificado

📋 Features

Necessidade identificada
Limitação encontrada
Sugestão de melhoria

Uso

## [ERR-20260321-001] connection_timeout

**Logged**: 2026-03-21T20:00:00Z
**Priority**: high
**Status**: resolved
**Area**: skills

### Error
Connection timeout ao instalar skill do ClawHub.

### Context
Tentando instalar skill com rede lenta.

### Resolution
Aumentar timeout para 60s em requests.

### Suggested Action
Adicionar retry automático com backoff.

Promoção

Aprendizados importantes são promovidos para:

AGENTS.md - Conhecimento do agente
TOOLS.md - Notas de ferramentas
SKILL.md - Melhorias de skills

Instalação

clawhub install aprendizado-continuo

Em Português

Esta skill foi criada especialmente para a comunidade brasileira ter auto-melhoria em português.

#aprendizado #learning #self-improvement #portugues #brasil

安全使用建议

This skill is an instruction-only blueprint for an "auto-improvement" workflow rather than an implemented tool. Before installing or enabling it: - Understand that there is no shipped code; any automation would be performed by the agent executing these vague instructions. Ask how the agent will detect errors and where it will write files. - Restrict write access: ensure the agent cannot modify sensitive files or skill definitions unless you explicitly allow it. Specifically, review and sandbox any behavior that would write to AGENTS.md, TOOLS.md or SKILL.md (these can affect agent behavior and documentation). - Prefer explicit rules: ask the author (or update SKILL.md) to specify exact capture sources, allowed file paths, formatting rules, and approval workflows for promoted changes. - Verify provenance: metadata is inconsistent (top-level listing shows no homepage while clawhub.json points to a GitHub URL). Confirm the source repository and review commit history before trusting automatic promotions. - If you want automation, implement or require a concrete, auditable component (script, webhook, or CI job) that you can inspect rather than relying on freeform agent actions. Given the vagueness about what the agent should do and where it may write, proceed with caution and limit autonomous write permissions until you have a concrete, reviewed implementation.

功能分析

Type: OpenClaw Skill Name: aprendizado-continuo Version: 1.0.0 The skill is a documentation and self-improvement framework designed to log errors, user corrections, and learnings into a local '.learnings/' directory. It contains no executable code, network requests, or instructions for data exfiltration. The logic is focused entirely on maintaining markdown-based logs to improve agent performance, which is consistent with its stated purpose in SKILL.md and clawhub.json.

能力评估

⚠ Purpose & Capability

The name and description claim automatic capture and promotion of errors into AGENTS.md, TOOLS.md and SKILL.md. However, the package contains no code or install steps — only prose describing a folder structure and example entries. There is no concrete mechanism (webhook, logger, file-watcher, or CLI tool) included to perform the "auto" behavior. Asking an agent to automatically modify those files is plausible, but the requested artifacts (none) are disproportionate to the claimed automation and leave substantial implementation discretion to the agent.

⚠ Instruction Scope

SKILL.md is high-level and vague: it defines a .learnings/ layout, capture triggers and example log format, and states that important learnings are "promoted" to AGENTS.md/TOOLS.md/SKILL.md. It does not specify boundaries, authorization, or where those target files live. That vagueness grants an agent broad discretion to read or write repository files and decide what counts as an error/learning — potentially modifying skill documentation or agent configuration without explicit constraints.

✓ Install Mechanism

There is no install spec and no code to install. This is low-risk from an installation/execution vector perspective because nothing is downloaded or extracted by the registry package itself.

✓ Credentials

The skill declares no required environment variables, credentials, or config paths. No direct requests for secrets are present. However, because the instructions encourage writing/promoting content into AGENTS.md/TOOLS.md/SKILL.md, an agent implementing this could be given file-system write access and potentially access other repository files; that operational privilege is not explicitly scoped by the skill.

ℹ Persistence & Privilege

always:false and normal agent invocation are set (no forced inclusion). Still, the skill's purpose is to alter documentation files (including SKILL.md), which implies the agent may be instructed to modify skill documentation or configuration. If the agent is allowed to run autonomously with write permissions, that increases blast radius. The skill itself does not request persistent system presence or special privileges, but its intended actions involve persistence (writing markdown files).

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install aprendizado-continuo
安装完成后，直接呼叫该 Skill 的名称或使用 /aprendizado-continuo 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

- Primeira versão do aprendizado-continuo lançada. - Captura automática de erros, correções, aprendizados e solicitações de features. - Sistema estruturado em português com diretório `.learnings/` para registro e acompanhamento. - Aprendizados promovidos automaticamente para AGENTS.md, TOOLS.md e SKILL.md. - Foco em auto-melhoria contínua para agentes da comunidade brasileira.

元数据

Slug aprendizado-continuo

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题