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Agent Skill · 研究检索

goodvibes-memory(好心情记忆)

goodvibes-memory 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

goodvibes-memory 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,权限为需要联网;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 39,365。

总安装 1,423周安装 57GitHub Stars 6下载 461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:goodvibes-memory(好心情记忆)
来源仓库:https://github.com/mgd34msu/goodvibes-plugin
仓库路径:skills/goodvibes-memory
安装命令:
npx skills add https://github.com/mgd34msu/goodvibes-plugin --skill goodvibes-memory
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/mgd34msu/goodvibes-plugin --skill goodvibes-memory

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。

goodvibes-memory 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。通过 npx skills add 命令从指定仓库安装并使用该技能。安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/goodvibes-memory

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/mgd34msu/goodvibes-plugin --skill goodvibes-me…;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

    它需要需要联网,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

goodvibes-memory 怎么安装?

在终端执行 npx skills add https://github.com/mgd34msu/goodvibes-plugin --skill goodvibes-memory。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

goodvibes-memory 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。

goodvibes-memory 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

goodvibes-memory 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。

goodvibes-memory 用的人多吗?

公开数据是累计安装 1,423 次,近一周安装 57 次,下载 461 次,GitHub 6 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。

goodvibes-memory 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
goodvibes-memory

好心情记忆 · 本页

1,4236需要联网未明确通过

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

Resources

scripts/
  validate-memory-usage.sh
references/
  schemas.md

GoodVibes Memory Protocol

The memory system enables cross-session learning by capturing decisions, patterns, failures, and preferences in structured JSON files. Every agent must read memory before starting work and write to it after completing work.

Why This Matters

Without memory:

  • Agents repeat known failures
  • Proven patterns are rediscovered each session
  • Architectural decisions are forgotten or violated
  • Project-specific preferences aren't applied

With memory:

  • Failures are logged with prevention strategies
  • Patterns are reused consistently
  • Decisions guide future work
  • Preferences ensure consistency

File Structure

.goodvibes/
|-- memory/           # Structured JSON (machine-readable)
|   |-- decisions.json    # Architectural decisions
|   |-- patterns.json     # Proven approaches
|   |-- failures.json     # Past errors + resolutions
|   |-- preferences.json  # Project conventions
|   +-- index.json        # Index file (optional)
+-- logs/             # Markdown logs (human-readable)
    |-- activity.md       # Completed work log
    |-- decisions.md      # Decision log with context
    +-- errors.md         # Error log with resolution

BEFORE Starting Work (Read Phase)

Always check memory files before implementing ANY task. Use keyword-based searches to find relevant entries.

1. Check failures.json

Purpose: Avoid repeating known failures.

How:

# Use precision_read to read the file
precision_read:
  files:
    - path: .goodvibes/memory/failures.json
  verbosity: standard

# Search for keywords matching your task
# Example keywords: "precision_fetch", "config", "auth", "API", "build"

What to look for:

  • keywords field matches your task (e.g., searching for "auth" finds authentication failures)
  • error field describes a similar problem
  • context field matches your current situation

If found:

  • Read resolution -- how was it fixed?
  • Read prevention -- how to avoid it?
  • Apply the prevention strategy

2. Check patterns.json

Purpose: Use proven approaches instead of inventing new ones.

How:

precision_read:
  files:
    - path: .goodvibes/memory/patterns.json
  verbosity: standard

What to look for:

  • keywords matches your task type
  • when_to_use describes your situation
  • name suggests a relevant pattern

If found:

  • Read description -- what's the pattern?
  • Check example_files -- where is it used?
  • Follow the pattern unless there's a compelling reason not to

3. Check decisions.json

Purpose: Respect prior architectural decisions.

How:

precision_read:
  files:
    - path: .goodvibes/memory/decisions.json
  verbosity: standard

What to look for:

  • scope includes files you'll modify
  • category matches your domain (e.g., "architecture", "pattern", "library")
  • status is "active" (not "superseded" or "reverted")

If found:

  • Read what and why -- understand the decision
  • If your task conflicts with the decision: flag to orchestrator before proceeding
  • If your task aligns with the decision: follow it

4. Check preferences.json

Purpose: Apply project-specific conventions.

How:

precision_read:
  files:
    - path: .goodvibes/memory/preferences.json
  verbosity: standard

What to look for:

  • key matches your domain (e.g., "category.preference_name")

If found:

  • Apply the value preference
  • Respect the reason rationale

Search Strategy

Manual keyword matching: Read the file and scan for keywords related to your task.

Example:

  • Task: "Add authentication with Clerk"
  • Keywords to search: auth, clerk, authentication, login, session
  • Check failures.json for past auth failures
  • Check patterns.json for auth patterns
  • Check decisions.json for auth library decisions

Scope filtering: Focus on entries where scope includes files you'll modify.


AFTER Completing Work (Write Phase)

Log to memory after completing a task, resolving an error, or making a decision. Always write to BOTH JSON (machine-readable) and Markdown (human-readable).

When to Write

SituationWrite to
Task passes reviewactivity.md + optionally patterns.json/decisions.json
Error resolvederrors.md + failures.json
Decision madedecisions.md + decisions.json
Never writeTrivial fixes, no new patterns, no decisions

After Task Passes Review

1. Always log to activity.md

Format:

## YYYY-MM-DD: [Brief Title]

**Task**: [What was the goal?]

**Plan**: [Approach taken, or N/A]

**Status**: COMPLETE

**Completed Items**:
- [List of what was accomplished]

**Files Modified**:
- [List of changed files with brief description]

**Review Score**: [X/10]

**Commit**: [commit SHA]

---

2. Optionally add to patterns.json (if a reusable pattern emerged)

Only add if:

  • The approach is reusable across multiple files/tasks
  • It's non-obvious (not standard practice)
  • It solves a specific problem well

Schema:

{
  "id": "pat_YYYYMMDD_HHMMSS",
  "name": "PatternNameInPascalCase",
  "description": "What the pattern does and why it works",
  "when_to_use": "Situation where this pattern applies",
  "example_files": ["path/to/file.ts", "another/example.ts"],
  "keywords": ["searchable", "terms"]
}

3. Optionally add to decisions.json (if an architectural decision was made)

Only add if:

  • A choice was made between multiple approaches
  • The decision affects future work
  • It has scope beyond this single task

Schema:

{
  "id": "dec_YYYYMMDD_HHMMSS",
  "date": "YYYY-MM-DDTHH:MM:SSZ",
  "category": "library|architecture|pattern|convention",
  "what": "What was decided",
  "why": "Rationale for the decision",
  "scope": ["files/directories affected"],
  "confidence": "high | medium | low",
  "status": "active|superseded|reverted"
}

After Error Resolved

1. Always log to errors.md

Format:

## YYYY-MM-DD HH:MM - [ERROR_CATEGORY]

**Error**: [Brief description]

**Context**:
- Task: [What were you doing?]
- Agent: [Which agent encountered it?]
- File(s): [Affected files]

**Root Cause**: [Why did it happen?]

**Resolution**: [How was it fixed? Or UNRESOLVED]

**Prevention**: [How to avoid it in the future?]

**Status**: RESOLVED | UNRESOLVED

---

2. Always add to failures.json (with full context)

Schema:

{
  "id": "fail_YYYYMMDD_HHMMSS",
  "date": "YYYY-MM-DDTHH:MM:SSZ",
  "error": "Brief error description",
  "context": "What task was being performed",
  "root_cause": "Technical explanation of why it failed",
  "resolution": "How it was fixed (or UNRESOLVED)",
  "prevention": "How to avoid this failure in the future",
  "keywords": ["searchable", "error-related", "terms"]
}

Error categories (for errors.md):

  • TOOL_FAILURE -- Precision tool or native tool failed
  • AGENT_FAILURE -- Agent crashed or failed to complete task
  • BUILD_ERROR -- TypeScript compilation, build step failed
  • TEST_FAILURE -- Test suite failed
  • VALIDATION_ERROR -- Validation, linting, or format checking failed
  • EXTERNAL_ERROR -- API, network, dependency issue
  • UNKNOWN -- Error category could not be determined

After Decision Made

1. Always log to decisions.md

Format:

## YYYY-MM-DD: [Decision Title]

**Context**: [What situation required a decision?]

**Options Considered**:
1. **[Option A]**: [Description + trade-offs]
2. **[Option B]**: [Description + trade-offs]

**Decision**: [What was chosen]

**Rationale**: [Why this option was best]

**Implications**: [What this means for future work]

---

2. Always add to decisions.json

See schema in "After Task Passes Review" section above.


ID Format

Use timestamp-based IDs to avoid needing to read existing entries before writing:

dec_YYYYMMDD_HHMMSS   # Decisions
pat_YYYYMMDD_HHMMSS   # Patterns
fail_YYYYMMDD_HHMMSS  # Failures
pref_YYYYMMDD_HHMMSS  # Preferences

Example: dec_20260215_143022 for a decision made on 2026-02-15 at 14:30:22

Collision risk: Negligible unless two agents write to the same file in the same second. The timestamp provides sufficient uniqueness.


First Write Check

Before first write to any memory/log file, check if it exists:

For JSON files

If file doesn't exist, create with bare array:

[]

For Markdown files

If file doesn't exist, create with header:

# [File Name]

Log of [description].

---

Use precision_read first:

precision_read:
  files:
    - path: .goodvibes/memory/decisions.json
  verbosity: count_only  # Just check existence

If exists: false, create the file before appending.


Common Mistakes

Don't Do This

  • Don't skip reading memory -- You'll repeat failures and violate decisions
  • Don't write for trivial work -- Only log meaningful patterns/decisions/failures
  • Don't use random IDs -- Use timestamp-based IDs (no need to read existing entries)
  • Don't forget prevention field -- Failures without prevention strategies aren't useful
  • Don't log to JSON only -- Always write to BOTH JSON and Markdown
  • Don't create duplicate entries -- Search keywords first to check if pattern/failure already exists

Do This

  • Do read failures.json first -- Check for known issues before starting
  • Do search by keywords -- Manual keyword matching is fast and effective
  • Do include full context -- Root cause + resolution + prevention for failures
  • Do use timestamp IDs -- No collision risk, no need to read existing entries
  • Do log to both formats -- JSON for machines, Markdown for humans
  • Do update last_updated -- Update timestamp when modifying index.json

Validation

Use the scripts/validate-memory-usage.sh script to verify compliance:

# Validate memory protocol usage
bash plugins/goodvibes/skills/protocol/goodvibes-memory/scripts/validate-memory-usage.sh \
  session-transcript.jsonl \
  .goodvibes/memory/

# Exit code 0 = compliant
# Exit code 1 = violations found

The script checks:

  • Memory files read at task start
  • Activity logged after task completion
  • Failures logged when errors resolved
  • Patterns logged when reusable approaches discovered

Quick Reference

Read Phase Checklist

  • Read failures.json -- keyword search for similar errors
  • Read patterns.json -- keyword search for proven approaches
  • Read decisions.json -- scope search for relevant decisions
  • Read preferences.json -- apply project conventions

Write Phase Checklist

  • Log to activity.md after task completion
  • Add to patterns.json if reusable pattern discovered
  • Add to decisions.json if architectural decision made
  • Log to errors.md + failures.json if error resolved
  • Log to decisions.md + decisions.json if choice made
  • Update last_updated timestamp in JSON files
  • Use timestamp-based IDs (no collisions)

Examples

Example: Reading Failures Before Starting Auth Task

# Step 1: Read failures.json
precision_read:
  files:
    - path: .goodvibes/memory/failures.json
  verbosity: standard

# Step 2: Manually search for keywords
# Keywords: "auth", "authentication", "clerk", "oauth", "token"
# Found: fail_20260210_160000 - "Service registry reads empty services"
# Context: OAuth token configuration issue
# Prevention: "Always use nested config format for services"

# Step 3: Apply prevention strategy
# Use nested format when configuring auth service

Example: Writing Pattern After Implementing Feature

# Step 1: Check if file exists
precision_read:
  files:
    - path: .goodvibes/memory/patterns.json
  verbosity: count_only

# Step 2: Read existing patterns to avoid duplicates
precision_read:
  files:
    - path: .goodvibes/memory/patterns.json
  verbosity: standard

# Step 3: Add new pattern (if not duplicate)
precision_edit:
  files:
    - path: .goodvibes/memory/patterns.json
      operations:
        - type: insert
          search: '"patterns": ['
          content: |
            {
              "id": "pat_20260215_143022",
              "name": "AuthServiceNesting",
              "description": "Auth services require nested config structure",
              "when_to_use": "When configuring auth providers in goodvibes.json",
              "example_files": [".goodvibes/goodvibes.json"],
              "keywords": ["auth", "config", "nested", "services"]
            },

Example: Logging Error Resolution

# Step 1: Log to errors.md
precision_edit:
  files:
    - path: .goodvibes/logs/errors.md
      operations:
        - type: insert_at_line
          line: 1
          content: |
            ## 2026-02-15 14:30 - BUILD_ERROR

            **Error**: TypeScript compilation failed with "Cannot find module 'clerk'"

            **Context**:
            - Task: Add Clerk authentication
            - Agent: Engineer
            - File(s): src/auth/clerk.ts

            **Root Cause**: Missing @clerk/nextjs package in dependencies

            **Resolution**: RESOLVED - Added package with `npm install @clerk/nextjs`

            **Prevention**: Always check package.json before importing new libraries

            **Status**: RESOLVED

            ---

# Step 2: Add to failures.json
precision_edit:
  files:
    - path: .goodvibes/memory/failures.json
      operations:
        - type: insert
          search: '['
          content: |
            {
              "id": "fail_20260215_143022",
              "date": "2026-02-15T14:30:22Z",
              "error": "TypeScript compilation failed - Cannot find module 'clerk'",
              "context": "Adding Clerk authentication to Next.js app",
              "root_cause": "Missing @clerk/nextjs package in package.json dependencies",
              "resolution": "RESOLVED - Installed package with npm install @clerk/nextjs",
              "prevention": "Before importing from a new package, verify it exists in package.json. Use precision_read to check package.json before adding imports.",
              "keywords": ["typescript", "clerk", "module", "dependency", "package.json", "build-error"]
            },

Integration with Other Skills

  • precision-mastery: Use precision_read/precision_edit for memory file operations
  • error-recovery: Check failures.json as first step in error recovery
  • gather-plan-apply: Include memory read in discovery phase
  • review-scoring: Reviewers check if memory was consulted before work started

File Location

All memory files are relative to project root:

.goodvibes/
|-- memory/
|   |-- decisions.json
|   |-- patterns.json
|   |-- failures.json
|   +-- preferences.json
+-- logs/
    |-- activity.md
    |-- decisions.md
    +-- errors.md

Always use .goodvibes/memory/ and .goodvibes/logs/ as paths (relative to project root).

平台分布

Codex

38.88%
按下载量换算179

Claude

27.11%
按下载量换算125

Cursor

19.15%
按下载量换算88

Gemini CLI

10.35%
按下载量换算48

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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