Exécutez n'importe quel Skill dans Manus
en un clic

Exécutez n'importe quel Skill dans Manus en un clic

Commencer

agent-memory

Étoiles5

Forks3

Mis à jour2 juillet 2026 à 09:30

A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

Installation

Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.

Exécuter dans Manus

Source

ranbot-ai

ranbot-ai/awesome-skills

Ouvrir le dépôt GitHub Voir les dépôts du créateur

Téléchargement

Exécuter dans Manus

Métiers associésSOC

Basé sur la classification professionnelle SOC

Développeurs de logicielsProfessions informatiques et mathématiques·SOC 15-1252

SKILL.md

readonly

name	agent-memory
description	A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
category	AI & Agents
source	antigravity
tags	["node","markdown","mcp","ai","agent","workflow","design","document","security"]
url	https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/agent-memory

agentMemory Skill

When to Use

Use this skill when you need a hybrid memory system that provides persistent, searchable knowledge management for AI agents.

This skill extends your capabilities by providing a persistent, searchable memory bank that automatically syncs with project documentation.

Prerequisites

Node.js installed
Check if agentMemory is already installed in the project:
```
ls -la .agentMemory
```

Setup

Install Dependencies:
```
npm install
```
Build the Project:
```
npm run compile
```
Start the Memory Server: You need to run the MCP server to interact with the memory bank.
```
npm run start-server <project_id> <absolute_path_to_workspace>
```
Note: This skill typically runs as a background process or via an mcp-server configuration. ensuring it is running is key.

Capabilities (MCP Tools)

Once the server is running, you can use these tools:

`memory_search`

Search for memories by query, type, or tags.

Args: query (string), type? (string), tags? (string[])
Usage: "Find all authentication patterns" -> memory_search({ query: "authentication", type: "pattern" })

`memory_write`

Record new knowledge or decisions.

Args: key (string), type (string), content (string), tags? (string[])
Usage: "Save this architecture decision" -> memory_write({ key: "auth-v1", type: "decision", content: "..." })

`memory_read`

Retrieve specific memory content by key.

Args: key (string)
Usage: "Get the auth design" -> memory_read({ key: "auth-v1" })

`memory_stats`

View analytics on memory usage.

Usage: "Show memory statistics" -> memory_stats({})

Workflow

Initialization: The first time you run this in a project, it may attempt to import existing markdown memory banks from .kilocode/, .clinerules/, or .roo/.
Development Loop:
- Before Task: Search memory for relevant context.
- During Task: Use read/search to answer questions.
- After Task: Write new findings to memory.
Sync: Your writes are automatically synced to standard markdown files in the project.

Limitations

Use this skill only when the task clearly matches its upstream source and local project context.
Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

Plus depuis ce dépôt

même dépôt

code-polish

ranbot-ai/awesome-skills

Rewrites unprofessional code comments into clear ones and performs non-semantic cleanup. Use to professionalize code without altering logic or behavior.

2026-07-035

ab-testing

ranbot-ai/awesome-skills

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test th

2026-07-025

accint-commitments

ranbot-ai/awesome-skills

Triage acc's open promises and close them with honest real-world verdicts via acc_act(runtime="outcome").

2026-07-025

accint-frames

ranbot-ai/awesome-skills

Drain acc's deliberation queue — open/waiting brain_frames checkpointed by headless runs — via acc_act(runtime="continue").

2026-07-025

accint-solve

ranbot-ai/awesome-skills

Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.

2026-07-025

add-app-clip

ranbot-ai/awesome-skills

Add an iOS App Clip target to an Expo app. Use when the user mentions App Clip, AASA, apple-app-site-association, appclips, smart app banner, or wants to ship a lightweight iOS Clip invoked from a URL

2026-07-025

name	agent-memory
description	A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
category	AI & Agents
source	antigravity
tags	["node","markdown","mcp","ai","agent","workflow","design","document","security"]
url	https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/agent-memory

agentMemory Skill

When to Use

Use this skill when you need a hybrid memory system that provides persistent, searchable knowledge management for AI agents.

This skill extends your capabilities by providing a persistent, searchable memory bank that automatically syncs with project documentation.

Prerequisites

Node.js installed
Check if agentMemory is already installed in the project:
```
ls -la .agentMemory
```

Setup

Install Dependencies:
```
npm install
```
Build the Project:
```
npm run compile
```
Start the Memory Server: You need to run the MCP server to interact with the memory bank.
```
npm run start-server <project_id> <absolute_path_to_workspace>
```
Note: This skill typically runs as a background process or via an mcp-server configuration. ensuring it is running is key.

Capabilities (MCP Tools)

Once the server is running, you can use these tools:

`memory_search`

Search for memories by query, type, or tags.

Args: query (string), type? (string), tags? (string[])
Usage: "Find all authentication patterns" -> memory_search({ query: "authentication", type: "pattern" })

`memory_write`

Record new knowledge or decisions.

Args: key (string), type (string), content (string), tags? (string[])
Usage: "Save this architecture decision" -> memory_write({ key: "auth-v1", type: "decision", content: "..." })

`memory_read`

Retrieve specific memory content by key.

Args: key (string)
Usage: "Get the auth design" -> memory_read({ key: "auth-v1" })

`memory_stats`

View analytics on memory usage.

Usage: "Show memory statistics" -> memory_stats({})

Workflow

Initialization: The first time you run this in a project, it may attempt to import existing markdown memory banks from .kilocode/, .clinerules/, or .roo/.
Development Loop:
- Before Task: Search memory for relevant context.
- During Task: Use read/search to answer questions.
- After Task: Write new findings to memory.
Sync: Your writes are automatically synced to standard markdown files in the project.

Limitations

Use this skill only when the task clearly matches its upstream source and local project context.
Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.