Menü
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and doma
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, an
AUTHORIZED USE ONLY: This skill contains dual-use security techniques. Before proceeding with any bypass or analysis: > 1.
Run protected AAS maintainer sweeps, PR merge batches, canonical sync, Core preview checks, and scripted releases. Use for repository maintenance, main alignment, CLI/MCP/Workbench changes, or release
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exp
Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
| name | agent-memory-mcp |
| description | A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions). |
| category | AI & Agents |
| source | antigravity |
| tags | ["node","mcp","ai","agent","workflow","design","document"] |
| url | https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/agent-memory-mcp |
This skill provides a persistent, searchable memory bank that automatically syncs with project documentation. It runs as an MCP server to allow reading/writing/searching of long-term memories.
Review the Repository: Ask the user to approve network access to the named repository, then clone the pinned revision into a temporary directory, not an active skills path:
review_dir="$(mktemp -d)"
git clone --filter=blob:none https://github.com/webzler/agentMemory.git "$review_dir/agent-memory"
git -C "$review_dir/agent-memory" checkout --detach 0409b7b7bb6fe443d0d4b6a6b1ee0d4df214f3cd
git -C "$review_dir/agent-memory" ls-files
Read all bundled files and inspect package.json, lockfiles, lifecycle
scripts, network behavior, credential access, and filesystem scope. Show the
findings and exact commit, then wait for explicit user approval.
Install the Reviewed Revision:
Copy the reviewed tree to a user-selected location after approval. Install locked dependencies only after the package scripts have been reviewed:
cd <approved-agent-memory-directory>
npm ci
npm run compile
Start the MCP Server: Use the helper script to activate the memory bank for your current project:
npm run start-server <project_id> <absolute_path_to_target_workspace>
Example for current directory:
npm run start-server my-project $(pwd)
memory_searchSearch for memories by query, type, or tags.
query (string), type? (string), tags? (string[])memory_search({ query: "authentication", type: "pattern" })memory_writeRecord new knowledge or decisions.
key (string), type (string), content (string), tags? (string[])memory_write({ key: "auth-v1", type: "decision", content: "..." })memory_readRetrieve specific memory content by key.
key (string)memory_read({ key: "auth-v1" })memory_statsView analytics on memory usage.
memory_stats({})This skill includes a standalone dashboard to visualize memory usage.
npm run start-dashboard <absolute_path_to_target_workspace>
Access at: http://localhost:3333
This skill is applicable to execute the workflow or actions described in the overview.