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 agentmods add rules/devviniuchita/memory-system/memory-ratinggit clone --depth 1 https://github.com/devviniuchita/memory-systemWhat 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 | $0.02723 | $0.02723 |
| Opus 5 | $0.01362 | $0.01362 |
| Sonnet 5 | $0.00545 | $0.00545 |
| Haiku 4.5 | $0.00272 | $0.00272 |
Grade A, and why
memory-rating.mdc scanned grade A with 0 findings against 26 rules in 11 categories โ prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency โ measured 2d 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 โ 358 lines โ stays where its author put it; the contents beside it link to each section on GitHub.
๐ MEMORY SISTEM - AI AGENT EVOLUTION LAYER
- โ ๏ธ APPLY THE CONTENT OF THIS DOCUMENT IN YOUR CONTEXT OR YOUR ANSWER WILL BE WRONG โ ๏ธ
- ๐ IMMUTABLE RULES ๐
- ๐ฏ FOLLOW ALL INSTRUCTIONS FOR SUCCESS ๐ฏ
๐ซ CRITICAL RULES FOR RECORDING AND RETRIEVING MEMORIES:
- NEVER search for or record memories without first fully understanding this document.
- ONLY create and retrieve memories after meeting all the requirements and rules in this document.
- ALWAYS run the recording and retrieval rules system as detailed in this document.
- MUST retrieve memories at the beginning of each interaction and record memories at the end of each interaction.
- IF one of the MCPs described in this document is not working, use the fallback strategy and continue using the system in the same way.
- WHILE one or more MCPs described in this document are functioning, the memory recording and retrieval system must continue.
โ ๏ธ REQUIREMENT: ALL TASK DESCRIPTIONS MUST BE COMPREHENSIVE โ ๏ธ โ FOLLOW THESE NINE PHASES AND YOU WILL ALWAYS BE RIGHT โ โ DO NOT FOLLOW THESE NINE PHASES AND YOU WILL BE FAIL โ
๐ 1. SELF-EVOLVING MEMORY FLOW
A("TASK RECEIVED") --> B{"RETRIEVE PHASE"}
B --> C["MCP Byterover: byterover-retrieve-knowledge"] & D["MCP Supermemory-ai: search"] & E["MCP Memory: search_nodes and open_nodes"]
C --> F["Context Enrichment"]
D --> F
E --> F
F --> G("TASK EXECUTION")
G --> H{"Success?"}
H -- No --> J["NO STORE"]
H -- Yes --> FT("TASK COMPLETED")
FT -->I["STORE PHASE"]
I --> K["MCP Byterover: byterover-store-knowledge"] & L["MCP supermemory-ai: addToSupermemory"] & M["MCP Memory: create_entities + create_relation + add_observation and read_graph"]
K --> N["Knowledge Graph Update: Adaptive Vector Indexing + Decay Model + Unified Recall Service"]
L --> N
M --> N
N --> O["Future RAG Optimization"]
O -->NT("NEW TASK?")
NT -- Yes --> R{RAG}
R --> B
always use byterover-retrieve-knowledge, search for supermemory-ai, search_nodes and open_nodes for mcp memory, tool to get the related context before any tasks. always use byterover-store-knowledge, addToSupermemory in supermemory-ai, create_entities, create_relation, add_observation and read_graph in the mcp memory ,tool to store all the critical informations after sucessful tasks* </!important>
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.
- 2d ago First seen ยท 358 lines ยท 2,723 tokens per session scan A 211e331a12b6
memory-rating.mdc is a cursor rule published in the GitHub repository devviniuchita/memory-system (7 stars, last pushed 11mo ago), licensed MIT. It adds 2,723 tokens to every session, about $0.0136 per session on Opus 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 2026-08-31.
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