agentmemory is a persistent-memory system that lets AI coding agents retain and search information across sessions. It connects with several coding agents and MCP clients, storing knowledge with confidence scoring, lifecycle handling, knowledge graphs, and hybrid search. The catalogue contains agentmemory integrations such as skills, hooks, commands, a plugin, and an MCP component.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add rohitg00/agentmemory --skill agentmemory-hooksgit clone --depth 1 https://github.com/rohitg00/agentmemoryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rohitg00/agentmemory/agentmemory-hooks)<a href="https://agentmods.dev/skills/rohitg00/agentmemory/agentmemory-hooks"><img src="https://agentmods.dev/badge/skills/rohitg00/agentmemory/agentmemory-hooks/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rohitg00/agentmemory/agentmemory-hooks"><img src="https://agentmods.dev/badge/skills/rohitg00/agentmemory/agentmemory-hooks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.00501 |
| Opus 5.5 | $0.00017 | $0.00200 |
| Sonnet 5.5 | $0.00008 | $0.00100 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
agentmemory-hooks scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- agentmemory-hooks — 100% identical, 18 lines differ
- agentmemory-hooks — 100% identical, 18 lines differ
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The agentmemory plugin registers lifecycle hooks so memory is captured automatically. You do not have to call memory_save for routine work; the hooks observe tool use, prompts, and session boundaries and write observations for you.
Quick start
For Claude Code, install its plugin:
/plugin marketplace add rohitg00/agentmemory
/plugin install agentmemory
For Devin CLI and Devin Desktop, install the plugin and start a new session:
devin plugins install rohitg00/agentmemory#plugin
Run /hooks inside Devin to confirm the agentmemory hooks are loaded. Plugin hooks run only in local Devin sessions, not in cloud sessions.
Hermes and OpenClaw use their native integrations and lifecycle contracts. Follow the matching integration setup instructions and verify a real turn creates an observation. Installing shared skills or connecting MCP alone does not enable automatic capture. Watch recorded observations in the viewer at http://localhost:3113 when using the default port.
What the hooks do
- Session start and end frame each unit of work and let
handoffresume it. - Tool-use hooks capture what changed and why, the raw material for
recallandrecap. - Prompt-submit captures intent. Pre-compact preserves context before the host trims it.
- A post-commit hook links commits to sessions, which powers
commit-contextandcommit-history.
Important
- The plugin hooks capture by default without an LLM. Summary generation (
AGENTMEMORY_AUTO_COMPRESS) and hook context injection (AGENTMEMORY_INJECT_CONTEXT) are separate options. Native integrations have their own recall/capture settings; inspect the host configuration instead of assuming these flags control every plugin. - If observations are missing, confirm the plugin is enabled and the server is running. See TROUBLESHOOTING.md.
See also
- agentmemory-config for the capture and injection flags.
- The handoff, recap, and session-history skills consume what these hooks record.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago Changed · +8 lines d20fb219252a
- 9d ago Changed 1363767d4dbf
- 1mo ago First seen · 40 lines · 42 tokens per session scan A 1ce38dac7869
agentmemory-hooks is a skill published in the GitHub repository rohitg00/agentmemory (29,807 stars, last pushed yesterday), licensed Apache-2.0. It adds 42 tokens to every session and 501 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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last30Days
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kb-research
Structured approach to finding and synthesizing information from the user's knowledge base.
md-fetch-summarize
Fetch a URL and return a concise markdown summary of its content. Read-only: no files are written; the summary is returned as output only. Use when asked to "fetch and summarize", "summarize this URL", "what does this page say", or "get the content of ". Proactively suggest when the user pastes a URL and asks what it…