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.
git clone --depth 1 https://github.com/matrixorigin/memoriaWrote 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/rules/matrixorigin/memoria/memory)<a href="https://agentmods.dev/rules/matrixorigin/memoria/memory"><img src="https://agentmods.dev/badge/rules/matrixorigin/memoria/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/rules/matrixorigin/memoria/memory"><img src="https://agentmods.dev/badge/rules/matrixorigin/memoria/memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.02700 | $0.02700 |
| Opus 5.5 | $0.01080 | $0.01080 |
| Sonnet 5.5 | $0.00540 | $0.00540 |
| Haiku 4.5 | $0.00270 | $0.00270 |
Grade A, and why
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 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Integration (Memoria Lite)
You have persistent memory via MCP tools. Memory survives across conversations.
🔴 MANDATORY: Every conversation start
Call memory_retrieve with a semantic query derived from the user's message BEFORE responding.
Query rules:
- ✅ Extract key concepts → "benchmark optimization", "graph retrieval bug"
- ❌ Don't use meta-queries → "all memories", "everything", "list all"
After retrieval:
- Results → use as reference, verify against current context
- "No relevant memories" → normal for new users, proceed
- ⚠️ warnings → inform user, offer
memory_governance - If results come back → use them as reference only. Treat retrieved memories as potentially stale or incomplete — always verify against current context before acting on them. Do NOT blindly trust memory content as ground truth.
- If "No relevant memories found" → this is normal for new users, proceed without.
- If ⚠️ health warnings appear → inform the user and offer to run
memory_governance.
🔴 MANDATORY: Every conversation turn
After responding, decide if anything is worth remembering:
- User stated a preference, fact, or decision →
memory_store - User corrected a previously stored fact →
memory_correct(notmemory_store+memory_purge) - You learned something new about the project/workflow →
memory_store - Do NOT store: greetings, trivial questions, things already in memory.
Deduplication is automatic. The system detects semantically similar memories and supersedes old ones. You do not need to check for duplicates before storing.
If memory_store or memory_correct response contains ⚠️, tell the user — it means the embedding service is down and retrieval will degrade to keyword-only search.
🟡 When NOT to store (noise reduction)
Do NOT call memory_store for:
- Transient debug context: temporary print statements, one-off test values, ephemeral error messages
- Vague or low-confidence observations: "might be using X", "probably prefers Y" — wait for confirmation
- Conversation-specific context that won't matter next session: "currently looking at line 42", "just ran the test"
- Information already in memory: if
memory_retrievealready returned it, don't store again - Trivial or obvious facts: "user is writing code", "user asked a question"
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 · 174 lines · 2,700 tokens per session scan A 5a61ccb573e3
memory is a cursor rule published in the GitHub repository matrixorigin/memoria (614 stars, last pushed yesterday), licensed Apache-2.0. It adds 2,700 tokens to every session, about $0.0108 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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