OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.
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 LeoYeAI/openclaw-master-skills --skill agent-memorygit clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skillsWrote 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/leoyeai/openclaw-master-skills/agent-memory)<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/agent-memory"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/agent-memory/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/leoyeai/openclaw-master-skills/agent-memory"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/agent-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00023 | $0.00358 |
| Opus 5.5 | $0.00009 | $0.00143 |
| Sonnet 5.5 | $0.00005 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
agent-memory 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 7d 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.
What it actually says
AgentMemory Skill
Persistent memory system for AI agents. Remember facts, learn from experience, and track entities across sessions.
Installation
clawdhub install agent-memory
Usage
from src.memory import AgentMemory
mem = AgentMemory()
# Remember facts
mem.remember("Important information", tags=["category"])
# Learn from experience
mem.learn(
action="What was done",
context="situation",
outcome="positive", # or "negative"
insight="What was learned"
)
# Recall memories
facts = mem.recall("search query")
lessons = mem.get_lessons(context="topic")
# Track entities
mem.track_entity("Name", "person", {"role": "engineer"})
When to Use
- Starting a session: Load relevant context from memory
- After conversations: Store important facts
- After failures: Record lessons learned
- Meeting new people/projects: Track as entities
Integration with Clawdbot
Add to your AGENTS.md or HEARTBEAT.md:
## Memory Protocol
On session start:
1. Load recent lessons: `mem.get_lessons(limit=5)`
2. Check entity context for current task
3. Recall relevant facts
On session end:
1. Extract durable facts from conversation
2. Record any lessons learned
3. Update entity information
Database Location
Default: ~/.agent-memory/memory.db
Custom: AgentMemory(db_path="/path/to/memory.db")
What ships with it
9 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.
- 7d ago Changed · +5 lines · +23 tokens per session 124935b44c39
- 2mo ago First seen · 67 lines · 0 tokens per session scan A 7de6c27f611b
agent-memory is a skill published in the GitHub repository LeoYeAI/openclaw-master-skills (2,168 stars, last pushed 6d ago), licensed MIT. It adds 23 tokens to every session and 358 once invoked, about $0.0001 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 2026-09-03.
agent-memory compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| agent-memoryLeoYeAI/openclaw-master-skills | Skill | 2.2k | 6d ago | MIT | A | 23 | Claude Code, Codex |
| context-degradationagent-skills-hub/agent-skills-hub | Skill | 128 | 1mo ago | MIT | A | 21 | Claude Code, Codex |
| context-compressionagent-skills-hub/agent-skills-hub | Skill | 128 | 1mo ago | MIT | A | 13 | Claude Code, Codex |
| context-optimizationagent-skills-hub/agent-skills-hub | Skill | 128 | 1mo ago | MIT | A | 13 | Claude Code, Codex |
| gossipcatgossipcat-ai/gossipcat-ai | Skill | 41 | 24d ago | MIT | A | 50 | Claude Code, Codex |
| cortex-mem-mcpsopaco/cortex-mem | Skill | 317 | 3mo ago | MIT | A | 72 | Claude Code |
| openclaw-memory-docsdavidtoby/agent-skills | Skill | 11 | yesterday | MIT | A | 27 | Claude Code, Codex |