SimpleMem is a long-term memory system for large-language-model agents that compresses, stores, and retrieves text and multimodal memories using semantic search. It is used with AI platforms that support MCP or Python to give agents persistent memory across text, images, audio, and video. Its catalogue skill supports workflows for using SimpleMem.
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 aiming-lab/SimpleMem --skill simplemem-skillgit clone --depth 1 https://github.com/aiming-lab/SimpleMemWrote 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/aiming-lab/simplemem/simplemem-skill)<a href="https://agentmods.dev/skills/aiming-lab/simplemem/simplemem-skill"><img src="https://agentmods.dev/badge/skills/aiming-lab/simplemem/simplemem-skill/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/aiming-lab/simplemem/simplemem-skill"><img src="https://agentmods.dev/badge/skills/aiming-lab/simplemem/simplemem-skill.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 | $0.00058 | $0.00845 |
| Opus 5.5 | $0.00023 | $0.00338 |
| Sonnet 5.5 | $0.00012 | $0.00169 |
| Haiku 4.5 | $0.00006 | $0.00085 |
Grade A, and why
simplemem-skill 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SimpleMem Skill
Persistent conversational memory across sessions.
Proactive Usage
Save memories when discovering valuable dialogue:
- Important decisions or commitments made in conversation
- Complex information that may be referenced later
- Context from long discussions worth preserving
- Solutions to problems that took effort to uncover
Check memories before:
- Answering questions about past conversations
- Resuming work from previous sessions
- Building on earlier discussion topics
Quick Start
# Add a dialogue
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py add --speaker "Alice" --content "Meet Bob tomorrow at 2pm"
# Query memories
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py query --question "When should Alice meet Bob?"
Operations
Save
Add single dialogue:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py add --speaker "User" --content "Your message here"
With timestamp (ISO 8601):
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py add --speaker "Alice" --content "Message" --timestamp "2026-01-17T14:00:00Z"
Query
Semantic query with answer:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py query --question "What did Alice say about meetings?"
With reflection for deeper analysis:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py query --question "Your question" --enable-reflection
Raw retrieval:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py retrieve --query "Alice meetings" --top-k 5
Maintain
View statistics:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py stats
Clear all memories:
# Use with caution - irreversible
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py clear --yes
Batch Import
For importing conversation histories from JSONL files, see references/import-guide.md.
What ships with it
22 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.
- .gitignore 234 B
- references/architecture.md 2.6 KB
- references/cli-reference.md 2.8 KB
- references/import-guide.md 1.2 KB
- references/openrouter-guide.md 2.3 KB
- references/requesty-guide.md 2.5 KB
- requirements.txt 120 B
- scripts/cli_persistent_memory.py 9.1 KB runs code
- src/config.py.example 2.9 KB
- src/core/__init__.py 222 B runs code
- src/core/answer_generator.py 5.0 KB runs code
- src/core/hybrid_retriever.py 38 KB runs code
- src/core/memory_builder.py 17 KB runs code
- src/database/vector_store.py 9.7 KB runs code
- src/main.py 9.3 KB runs code
- src/models/__init__.py 110 B runs code
- src/models/memory_entry.py 2.8 KB runs code
- src/utils/__init__.py 137 B runs code
- src/utils/embedding.py 4.5 KB runs code
- src/utils/llm_client.py 3.6 KB runs code
- src/utils/openrouter.py 7.4 KB runs code
- src/utils/requesty.py 7.1 KB runs code
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.
- 1mo ago First seen · 130 lines · 58 tokens per session scan A 2944c9d9a8e4
simplemem-skill is a skill published in the GitHub repository aiming-lab/SimpleMem (3,848 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 845 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.
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