rohitg00/agentmemory

Agent skills in the GitHub repository rohitg00/agentmemory, each with its code score out of 100.

#1 Persistent memory for AI coding agents based on real-world benchmarks

Repository score

73 / 100 B

Skills

17

Verified

3

Average skill score

69

GitHub stars

30,311

License

Apache-2.0

Open rohitg00/agentmemory on GitHub

17 skills in this repository

1. recall

   Search agentmemory for past observations, sessions, and learnings about a topic using hybrid BM25 plus vector plus graph search. Use when the user says "recall", "what did we do a…

   Verified84B
2. remember

   Save an insight, decision, or learning to agentmemory's long-term storage with searchable concept tags. Use when the user says "remember this", "save this", "note that", "don't fo…

   Verified82B
3. handoff

   Resume the most recent agent session for the current working directory, leading with any unanswered question. Use when the user says "where were we", "resume", "handoff", "pick up…

   Verified80B
4. recap

   Summarize the last N agent sessions for the current project, grouped by date, with highlight observations per session. Use when the user asks "recap", "what have we been doing", "…

   79B
5. forget

   Delete selected durable memories from agentmemory after showing them and getting explicit confirmation. Use when the user says "forget this", "delete memory", "remove that note",…

   78B
6. lesson

   Save a correction or hard-won rule as a confidence-weighted lesson that resurfaces before similar work. Use when the user corrects your approach, says "learn this", "always" or "n…

   77B
7. commit-context

   Trace a file, function, or line back to the agent session that produced its current commit. Use when the user asks "why is this code here", "what was the agent doing when this cha…

   73B
8. commit-history

   List recent git commits linked to agent sessions, optionally filtered by branch or repo. Use when the user asks "show agent commits", "what has the agent shipped", "list linked co…

   73B
9. memory-discipline

   The session loop that makes agentmemory pay off, recall before starting work, save at decision points, learn from corrections. Use when starting a nontrivial task, after settling…

   71B
10. session-history

    Show what happened in recent past sessions on this project as a clean timeline. Use when the user asks "what did we do last time", "session history", "past sessions", or wants an…

    70B
11. agentmemory-config

    Set up and diagnose local agentmemory, including MCP, environment variables, ports, and feature flags. Use when getting started, checking a connection, enabling a feature, configu…

    68C
12. agentmemory-mcp-tools

    Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what…

    64C
13. agentmemory-agents

    How agentmemory wires into host coding agents via the connect command. Use when installing agentmemory into a specific agent, when asked which agents are supported, or when a conn…

    61C
14. write-agentmemory-skill

    The house format and rules for writing or updating an agentmemory skill. Use when adding a new skill, restructuring an existing one, or reviewing a skill contribution for consiste…

    61C
15. agentmemory-hooks

    The agentmemory plugin hooks that capture observations automatically across the agent session lifecycle. Use when explaining how memory gets captured without manual saves, when de…

    57C
16. agentmemory-rest-api

    The agentmemory HTTP REST API surface, the primary protocol for talking to the memory server. Use when calling agentmemory over HTTP, when MCP is unavailable and you need a fallba…

    52D
17. agentmemory-architecture

    How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, wh…

    45D

Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.