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 skills/lotargo/memory_plugin/using-memorynpx skills add Lotargo/memory_plugin --skill using-memorygit clone --depth 1 https://github.com/Lotargo/memory_pluginWhat 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 | $0.00124 | $0.06296 |
| Opus 5 | $0.00062 | $0.03148 |
| Sonnet 5 | $0.00025 | $0.01259 |
| Haiku 4.5 | $0.00012 | $0.00630 |
Grade A, and why
using-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 yesterday.
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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using Memory, Hybrid RAG Knowledge Engine & MCP Helper Tools
You have access to a persistent dual-layer memory engine supercharged with an Agent-Driven Knowledge Graph and general MCP integration helpers:
- Layer 1: Notebook Store (Key-Value Facts): Stores high-signal personal preferences, project conventions, and durable rules in clean Markdown.
- Layer 2: Curated RAG Knowledge Base: Preserves selected external findings, documentation, repositories, and technical guides that are likely to matter again.
- Layer 3: Agent-Driven Knowledge Graph: Connects Notebook facts (Layer 1) to specific Knowledge Base documents, sections, and exact line ranges (Layer 2).
- Integration Layer (General MCP Helpers): Quickly discovers connected MCP servers and identifies appropriate tools for specific tasks.
1. Tool Selection Decision Matrix
| Scenario / Intent | Target Tool | Key Parameters |
|---|---|---|
| User shares identity, tech stack preference, or workflow rule | remember |
fact (English), title (concise 2-5 word headline), kind (fact context or directive active instruction), scope, optional directory (workspace path), docId, startLine, endLine |
| User asks what you remember about them, the project, or linked docs | recall |
scope ("all", "global", "project", "list_projects"), mode ("full", "headers"), offset, limit, optional query, tags, since, until, directory / project (at session start in clients without auto-injection, MUST fetch all memories with scope: "all" without restrictive query filters) |
| Get a single fact's text and metadata by ID | get_fact |
id (metadata id e.g. "8f3a2c"), scope, optional directory |
| User corrects/updates or reclassifies an old saved fact | update_fact |
id (number/id/text), newText, optional kind, scope, optional directory |
| Replace a fact but keep a version trail | remember |
fact, supersedes (number/id/text), optional directory |
Protect a fact from accidental forget |
remember |
keep: true |
| Set a time-to-live on a fact | remember |
ttl ("90d", "2w", "24h", "12m") |
| Filter facts by keyword / tags / date | recall |
query, tags, since, until, optional directory |
| Show storage paths, versions, fact & RAG stats, git identity | memory_info |
optional directory |
| Connect a Notebook fact to a document, section, or line range | link_knowledge |
action ("link", "list_links", "get_doc_links"), factText, docId, startLine, endLine, relationType, optional directory |
| Register current Git project identity / migrate legacy stores | memory_info then link_project_memory when Registry: unlinked |
directory, optional remote |
| Remove path alias or purge project identity | unlink_project_memory |
directory, purge (boolean) |
| Move or merge project memories to new target identity | relink_project_memory |
directory, remote (target remote URL) |
| User asks to index a documentation URL, file, or repository | ingest_document |
content (text/file path/URL), type ("text", "file", "url"), title, path, scope (project default), optional directory |
| User asks a complex question about indexed docs or code | query_knowledge_base |
query, scope (all default), limit, instruction, generateEmbeddings, optional directory |
| User needs multiple queries executed in batch (comparisons, multi-topic) | batch_query_knowledge_base |
queries (array), scope (all default), limit, instruction, generateEmbeddings, optional directory |
| Read full raw content of an ambiguous/abstract document | manage_knowledge_base |
action: "read_document", docId |
| View DB stats, list indexed docs, read/delete docs, export/import snapshots | manage_knowledge_base |
action ("stats", "list", "read_document", "delete", "export_snapshot", "import_snapshot"), docId, snapshotPath, optional directory |
| Re-embed all documents after switching embedding model / dimension | reindex_knowledge_base |
model, dimension (optional; defaults to active config) |
| Discover available MCP servers and their specific purposes | list-mcp-tools |
— |
| Ask which MCP tool / server is suitable for a specific task | mcp-reminder |
task (string, e.g., "db migration") |
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.
- yesterday First seen · 261 lines · 124 tokens per session scan A 1fc5d6f78dee
using-memory is a skill published in the GitHub repository Lotargo/memory_plugin (2 stars, last pushed 7d ago), licensed MIT. It adds 124 tokens to every session and 6,296 once invoked, about $0.0006 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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